This course aims to develop the general theory of rings (especially commutative ones) and then study in some detail a new concept. That of a module over a ring. Both abelian groups and vector spaces may be viewed as modules and important structure theorems for both follow from the general theory. Fields are important objects of study in algebra since they provide a useful generalization of many number systems, such as the rational numbers, real numbers, and complex numbers. The theory of rings, modules and fields is key to many more advanced algebra courses e.g. Algebraic Number Theory and Commutative Algebra. It can also help with others, e.g. Galois Theory, Representation Theory and Algebraic Geometry.

## Syed Babar Ali School of

Science and Engineering

## List of courses (A-Z)

We offer a variety of courses in STEM education. Take a look and discover your area of interest. This will assist you in selecting the most suitable course.

### Fall 2024

### A

This course attempts to bridge the gap between the foundational quantum mechanics courses and actual research level work. Various students have indicated great interest in such a course (at least twenty), which supports the need that there is indeed great need for such a course. Moreover, with increasing interest in futuristic quantum technologies such as quantum computation and communication, this course should be of interest to students in CS and EE (who have taken the basic courses in quantum mechanics), but want to perform research in this area.

This is an intermediate-level course focusing on the application of probability theory to science and engineering disciplines. The first portion of the course reviews the basic probability theory with some examples chosen from science and engineering. Later portion of the course deals with moderately advanced topics that signify the use of probability theory in these disciplines. The topics covered in the course should help the students building a background for understanding and conducting research in computer and data sciences, estimation and learning, and other more general engineering problems. In particular, we will discuss random variables and expectations, joint and conditional distributions, random processes, queueing systems and Markov chains, confidence intervals, and prediction/learning/estimation theory.

### C

This intermediate course on classical mechanics introduces students to the Lagrangian and Hamiltonian formulations of classical mechanics. We will begin a quick review of the calculus of variation and then develop the Lagrangian formulation of mechanics. The treatment of the central-force problem will be revisited using the Lagrangian formulation followed by the mechanics in accelerating frames of reference. The last half of the course will deal with the Hamiltonian formulations, canonical transformations, and scattering and perturbation theory in classical mechanics.

The course's primary focus is to understand the theoretical foundation of some of the most widely used computational biology techniques. The principles and methods for pair-wise and multiple sequence analysis using hidden Markov models, phylogenetic analysis, protein sequence analysis and structure prediction are extensively covered. In addition systems biology is introduced at a glance with a significant amount of time spent on microarray analysis. The tutorials will provide hands-on training of programming in R and MATLAB to develop problem solving skills in computational biology research using scripting languages.

This course provides an introduction to computational biology, introducing the tools and techniques important to study and analyze genomic data. This course emphasises the fundamentals of nucleic acid and protein sequence analysis, phylogenetic analysis and the analysis of biological networks.

Operations research has had an increasingly great impact on the management of organizations, including business, government, and military. Operations research involves formulation of real life situations into mathematical models, and then developing optimal solutions by application of various algorithms. The purpose of this course is to provide an appreciation of various techniques used in operations research, and their application in developing optimal solutions for real life problems.

This course provides a conceptual and practical introduction to programming. The focus is on programming rather than the particular choice of programming language, with general principles being brought out through the study of ‘C/C++’. This course will equip students with tools and techniques to implement a given problem programmatically.

### D

This course covers the mathematical foundations of computer science. The aim is to introduce the students to the fundamental techniques of discrete mathematics, which may be employed in a variety of mathematical disciplines, including fields in theoretical computer science, such as, algorithms, data structures and complexity theory. An introduction to logic, proof techniques, sets, functions, and relations is made, along with an initiation to combinatorics, basic graph and tree structures. A very brief introduction to number theory and discrete probability is made. Problems are formed mathematically and solved using available tools and techniques.

Deep Learning is a hierarchical learning methodology based on artificial neural networks which are algorithms inspired by the structure and function of the brain. It has applications in wide-range of industries these days such as face-recognisers working at massive scales, robotics, speech translation, text analysis, improving customer experience, autonomous vehicles etc.

In this course we will take a “hands-on approach” and start will implementation of basic building blocks such as training a simple perceptron and move to design and train a deep convolution neural network. Course will concentrate in developing both mathematical knowledge and implementation capabilities. The implementations will be python based using TensorFlow and Keras. After establishing our foundation in convolutional neural networks we will start looking into applications of deep learning in both spatial as well as time-series data and explore various network architectures suited for each. The objective is to help you build a career in AI and Machine learning, to make you comfortable enough that you can understand various learning problems and develop your own deep learning based solutions.

This course explains how to go about designing complex, high-speed digital circuits and systems. The use of modern EDA tools in the design, simulation, synthesis and implementation is explored. Application of a hardware description language such as Verilog or VHDL to model digital systems at Behavior and RTL level is studied. Advanced methods of logic minimization and state-machine design are discussed. Design and implementation of digital system building blocks such as arithmetic circuits, datapaths, microprocessors, I/O modules/interfacing, UARTs, frequency generators, memories etc. is included. BIST and Scan techniques for testing of digital systems are also covered.

### E

Evolutionary ideas link different fields of biology. This course provides an evolutionary context to understand biology. We will review the history of evolutionary thoughts, the forces of evolution, and the need for an extended evolutionary synthesis theory. We will also study the application of evolutionary studies to medicine and agriculture.

Engineering models allow Scientists and Engineers to understand systems under study by performing experiments. Differential equations have been the main tool (models) for the mathematical analysis, comprehension, design and prediction of things that change. The emergence of digital computers has provided alternative methods for the approximate analysis of both natural and man-made systems through numerical solutions. This course describes both the analytical techniques for solving first-order and second-order differential equations as well as describes a wide range of unrelated physical phenomena that can be modelled through them. In addition, graphical and numerical methods for solving differential equations are introduced. Furthermore, separable partial differential equations (PDEs) and their boundary value problems are introduced through the classical Heat,

Wave and Laplace’s equation.

The course is a first introduction to Electricity and Magnetism. It will review static and dynamic electric and magnetic fields and their inter-relationships. Physical models will be presented throughout the course, with a sprinkling of computational exercises and in-class demonstrations.

### G

The intellectual framework of this course will introduce students to basic concepts in genetics and epigenetics. Both genetic and epigenetic inheritance patterns will be introduced with an emphasis how they influence our development. Different modules will cover classical genetics based on Mendelian laws and gene interactions which explain deviations from Mendel’s laws. In addition, microbial genetics will be explained to help understand how fundamentals of gene regulation were discovered. During this course, students will learn in great detail how forward and reverse genetics approaches in different model systems are employed to understand cellular function. Moreover, human genetics module will explain how genetics plays a major role by using alleles in humans to understand disease and development. Last but not the least, understanding quantitative genetics and population genetics will explain how mutagenic traits are investigated and how genes may evolve at a population level. How genetics has helped us understanding molecular and biochemical pathways of development is an important subject of this course.

### I

Introduction to Analysis II is the sequel to Introduction to Analysis I, and together these two courses constitute the foundations of real analysis in mathematics. This course is designed to prepare students for future advanced analysis and functional analysis courses. It lays the foundation for several other areas, such as complex analysis, topology, dynamical systems, quantum mechanics, and mathematical statistics. The rigorous treatment of the subject in terms of theory and examples gives students the flavor of mathematical reasoning and intuition for other advanced topics in mathematics. Topics covered are Open, closed, and compact sets of real numbers. Sequences and series of functions, point wise and uniform convergence. Power series and Taylor series. Metric spaces: basic notions generalized from the setting of the real numbers.

### L

In this Master's level course, students will learn through a systems thinking approach. We'll introduce key actors and stakeholders in the local and regional energy access landscape, all in pursuit of Sustainable Development Goal 7 (SDG 7). Throughout the course, we will use real-life case studies, reports, and data analysis, and highlight both best and worst practices in global, regional, national, and local energy solutions to enhance their understanding. "The purpose of the ""Local Energy Access Course"" is to empower participants with knowledge and skills related to energy access at the local level, with a specific focus on Pakistan. The course aims to:

1. Comprehensive Understanding: Provide students with a comprehensive understanding of the DRE sector, including Mini- and Micro-grids, standalone solar systems, grid integration and load considerations.

2. Problem Solving for SDG7: Equip students with skills to assess DRE challenges and propose solutions in alignment with SDG7.

3. Exploration of Options: Introduce various distributed generation options, from standalone solar home systems to micro-grids, while addressing drivers and barriers.

4. Sustainability Focus: Promote sustainability by integrating energy efficiency, sustainable energy practices, and environmental considerations.

5. Holistic Expertise: Enable students to analyze and contribute to localized and regional DRE solutions, utilizing the latest tools and data while opening up career and entrepreneurial opportunities. "

### M

This course is a rigorous survey of magnetism in condensed matter. It will connect the phenomenon of

magnetism and its various manifestations to atomic and electronic systems and their interactions. The

electronic systems could be localized or itinerant. We will traverse a trajectory of discussion wherein we will

find the origins of magnetism within angular momentum and start exploring the magnetism of isolated systems. We will then assemble these angular momentums into crystal structures and will begin exploring

the impact of crystal environments and interactions. We will spend considerable time on the exchange

interaction and how the interplay of exchange effects and crystal structure leads to long range magnetic

order of multiple kinds. We will investigate order and broken symmetry and look at specific examples of

magnetism in metals, glasses, low dimensional systems and will survey the burgeoning field of spintronics.

Introduces the principles of classical mechanics. Straight-line kinematics; motion in a plane; relative inertial frames and relative velocity; forces; particle dynamics with force; work, conservative forces, potential energy and conservation of energy; conservation of momentum, center of mass and the center of mass reference frame; rigid bodies and rotational dynamics; conservation of angular momentum; central force motions; simple harmonic motion, oscillations.

This course provides a comprehensive introduction to molecular biology and is designed for students interested in learning molecular mechanisms which control cellular processes in eukaryotes and prokaryotes. Topics include structure of nucleic acids and proteins, organization of genes, genomes, chromatin and chromosomes, DNA replication, repair, recombination, transcription, mRNA processing, protein synthesis and turnover, control of gene expression, signal transduction pathways, non-coding RNAs, evolution of biopolymers and origin of life.

### N

Linear Algebra is one of the most widely used topics in the mathematical sciences. In the course of Linear Algebra, we learnt standard techniques for basic linear algebra tasks, including the solution of linear systems, finding eigenvalues/eigenvectors and orthogonalisation of bases. However, these techniques are usually computationally too intensive to be used for the large matrices encountered in practical applications.

This course will focus on the fundamental concepts of numerical linear algebra introducing the practical issues to practical applications. It will teach you how to analyze and apply certain algorithms in a reliable and computationally efficient way.

We will focus on the following: direct and iterative methods for solving simultaneous linear equations; matrix factorization, decomposition, and transformation; conditioning, stability and efficiency; computation of eigenvalues and eigenvectors. Since many real-world problems ultimately reduce to linear algebra concepts

and algorithms, there will be a strong emphasis on understanding the advantages and disadvantages, as well as the limits of applicability for all the covered techniques. The course includes significant computing-related assignments that require computer use and basic programming skills (Python). The theoretical material will be assessed in an examination over LMS/Zoom.

### O

Operations research has had an increasingly great impact on the management of organizations, including business, government, and military. Operations research involves formulation of real life situations into mathematical models, and then developing optimal solutions by application of various algorithms. The purpose of this course is to provide an appreciation of various techniques used in operations research, and their application in developing optimal solutions for real life problems.

### P

This is the first course in Power Electronics. Students will learn about specific areas of application and the reasons Power Electronics is becoming popular in areas traditionally occupied by analog electronics. The course will cover applications in conversion and control of power using Power semiconductor devices, physics of their structure and operation and passive components in power circuits. Students will also learn the principles governing the operation of converters, different standard topologies, applications in power systems, motor drives, and applications in renewable energy sources.

### Q

This course builds upon the basic quantum algorithms that were covered in introductory quantum computing courses. This course starts with a discussion of the computational complexity of algorithms and then moves on to applied quantum algorithms. The major algorithms covered in this course are HHL algorithms for solution of algebraic equations, Hamiltonian simulation and variational quantum algorithms for simulating quantum systems such as molecules, quantum approximate optimization algorithms, and algorithms for quantum machine learning.

### R

This course has two parts. The first part deals with special theory of relativity. The second part deals with the application of the special theory in electrodynamics. We will begin with a detailed introduction of special theory, and will see how we can build up the magnetostatics and electromagnetics in free space just from the Coulomb’s law and the relativistic transformation of charges and force. We will also study the motion of charged particles in electromagnetic fields and the fields radiated by the relativistically moving charged particles. Lagrangian and Hamiltonian for the charged particles in the external electromagnetic fields will also be introduced.

### S

The Norwegian mathematician Sophus Lie (1842 - 1899) initiated the symmetry analysis of differential equations. Today, this area of research is actively engaged. In this course, we trace the mathematical idea of symmetry and provide the salient features of the Lie theory of transformation groups with applications to ordinary and partial differential equations. The Lie approach is a systematic way of unravelling exact solutions of ordinary and partial differential equations. It works for linear as well as for nonlinear differential equations.

The Norwegian mathematician Sophus Lie (1842 - 1899) initiated the symmetry analysis of differential equations. Today, this area of research is actively engaged. In this course, we trace the mathematical idea of symmetry and provide the salient features of the Lie theory of transformation groups with applications to ordinary and partial differential equations. The Lie approach is a systematic way of unravelling exact solutions of ordinary and partial differential equations. It works for linear as well as nonlinear differential equations.

### Summer 2024

### C

This course provides a conceptual and practical introduction to programming. The focus is on programming rather than the particular choice of programming language, with general principles being brought out through the study of ‘C/C++’. This course will equip students with tools and techniques to implement a given problem programmatically.

This is the first course of a two semester course sequence. This course covers limits, continuity, differentiation and its applications, integrals and techniques of integration, applications of integrals, early transcendental functions.

### F

This course has been designed to cover the modern experimental aspects of molecular and cellular biology. Students enrolled in this course are expected to have taken an introductory level course in molecular biology and a firm grasp of structure and function of nucleic acids and proteins.

### G

This course will introduce students to fundamental principles of game design and development. The course will conclude with a team-based project that will require students to design and implement a game of their choice using C# in the Unity game engine. Some Unity concepts will be explained in class, but students will be required to learn the engine outside class hours. Lecturers will be available for Unity guidance outside class hours.

### I

Quantum computers are the computers of future because they seem to be much faster than the current computers for many tasks. Many companies like IBM, Google, Microsoft are investing heavily to develop quantum computers and are making them available in the cloud at the initial stage. This course will be your first introduction and hands-on interaction with quantum computers. We will learn designing quantum algorithms and implementing them on actual quantum computers. The course is specifically designed for broader group of students to introduce quantum computer programming without requiring any previous knowledge of quantum physics. We will study algorithms to solve practical problems like searching a database, factoring prime numbers, optimization, etc. and demonstrate the quantum advantage over currently used classical computers. The algorithms will be implemented using QISKIT package in Python and students will learn to write the programs and run them on IBM’s quantum computers. This course will also cover all the syllabus of recently announced IBM’s certification exam for quantum developers.

This course introduces basic computational methods for understanding what nervous systems do and determining how they function. Specific topics that will be covered are:

- Single-neuron biophysics.

- Representation of information by spiking neurons.

- Example of information processing in neural networks.

We will explore the computational principles governing various aspects of the early mammalian visual system. We will use some basic scientific programming exercises to better understand the concepts and methods introduced in the course. The theoretical lectures are combined with student presentations of biological and experimental papers with the help of the instructor. The course primarily aims to build a basic theoretical foundation for understanding how the brain processes information.

### L

This is the first course of a two semester sequence in linear algebra. This course gives a working knowledge of: systems of linear equations, matrix algebra, determinants, eigenvectors and eigenvalues, finite-dimensional vector spaces, matrix representations of linear transformations, matrix diagonalization, changes of basis, Separable and first-order linear equations with applications, 2nd order linear equations with constant coefficients, method of undetermined coefficients, Systems of linear ODE's with constant coefficients, Solution by eigenvalue/eigenvectors, Non homogeneous linear systems.

### M

Introduces the principles of classical mechanics. Straight-line kinematics; motion in a plane; relative inertial frames and relative velocity; forces; particle dynamics with force; work, conservative forces, potential energy and conservation of energy; conservation of momentum, center of mass and the center of mass reference frame; rigid bodies and rotational dynamics; conservation of angular momentum; central force motions; simple harmonic motion, oscillations.

This course is intended to be a first introduction to quantum phenomena in nature. Quantum Mechanics forms the basis of our description of nature at small scales and a clear understanding of it is required to understand phenomena ranging from atoms and chemical bonding to semiconductors and nuclear physics. We will present a concise and comprehensive picture of quantum theory with emphasis on concept building. The concepts will be organized around the idea of wave particle duality and its consequences. Numerous applications to real world phenomena will be discussed throughout the course. The course also has a component that discusses the application of statistical ideas in physics and how it gives rise to our common understanding of phenomena involving heat and temperature in the form of laws of thermodynamics including their applications.

### O

Operations research has had an increasingly great impact on the management of organizations, including business, government, and military. Operations research involves formulation of real life situations into mathematical models, and then developing optimal solutions by application of various algorithms. The purpose of this course is to provide an appreciation of various techniques used in operations research, and their application in developing optimal solutions for real life problems.

### S

This is a first course in probability which provides preparation for further courses in stochastic processes, statistics, statistical mechanics and an understanding of the probability concepts essential for students who want to pursue studies in physical sciences, social sciences, economics, and engineering. The course starts with an introduction of probability terms and methods of computing simple and conditional probabilities. The concepts of discrete and random variables are covered. Special discrete and continuous probability distributions are explored with their real life applications.

### T

This is an introductory course on Astronomy which discusses the physical basis of our understanding of our place in the Cosmos. We will begin with our immediate surroundings to understand important questions about the phases of the moon, eclipses and how we use them to compute the distance scale of the solar system. We will then talk about the processes that power our sun and stars in general. The next step would be understanding the structure of the Universe as a whole as we know it from astronomical observations. We talk, in particular, about the expanding and accelerating Universe, and how we know it is in a phase of accelerated expansion. All along, we will be focused on why we think the way we think about our Cosmos. An illuminating feature of this course is understanding the skies around us whose detailed observational study has informed our understanding of the Universe and some of its fundamental physical principles. The course will also take a historical tour of our understanding of Cosmology beginning with the Greek models. The clear night skies of Gilgit-Baltistan will offer us observational evidence of what we will study. We will attempt to photograph the night sky, understand Astrology (and why it has nothing to do with science), and focus our telescope on various objects in the solar system.

### Spring 2024

### A

In this course we will study

Real-valued functions of several variables: Structure and Topology of Rn ; The limit and continuity of functions of n- variables; Partial derivatives and differentials of functions of several variables; The Chain Rule, Mean Value and Taylor’s Theorems.

Vector-valued functions of several variables: Linear Transformations and Matrices; Continuity and Differentiability of Transformations; Inverse function theorem and Implicit function theorem.

Integrals of functions of several variables (Very basic): Definition and Existence of the Riemann integral of several variables; Iterated and multiple integrals; Change of variables in multiple integrals.

The Advance Biochemistry course is designed to provide graduate students an understanding of detailed concepts in Biochemistry. Students will learn the concepts that would prepare them for research and scientific training. The topics such as Structure, Function and Analysis of Biomolecules; Enzymes and Drug Discovery; Role of H Bonding in Protein Stability and Glycobiology will be covered with the emphasis on critical analysis and research paper reading, discussion and presentation.

This course is designed to present the advanced concepts of the organic chemistry to understand more about the synthesis and reactivity of various classes of organic compounds. We will discuss the chemoselectivity, retrosynthetic analysis, rearrangement, asymmetric synthesis and synthesis and reactions of the classes of organic compounds like aromatic rings, aromatic heterocycles, electrophilic alkenes, organic compounds containing sulfur, boron, silicon and tin in more detail. The synthesis of natural products such as alkaloids, fatty acids, aromatic polyketides and terpenes mays also be discussed.

The last two centuries have seen many new branches of mathematics. Abstract Algebra is one such branch. Because of its vast applications in various disciplines of mathematics and also different subjects like Physics, Chemistry, Statistics and Computer Science, it becomes necessary to introduce this topic at the undergraduate – level Curriculum.

The aim of this course is to introduce students to the basic concepts of Abstract Algebra. To this end we will study Group Theory in depth, followed by a brief introduction to Rings (and Fields depending on the time frame in the online medium). This course is very important as it is a prerequisite for many advanced level courses in Pure Mathematics.

This course is designed with a biological applications centric approach towards probability and statistics. Students are not expected to bring in any

prior knowledge of probability or statistics! By the end of this course, each student should be able to understand the nature of data generated in

wet labs and analyze them accordingly. A project will be offered at the end of the course and it is expected that students should be able to read

on advanced techniques and apply them independently.

This is the third course in a serious of undergraduate courses on programming. Compared to introductory programming courses, this course is concerned with systematically solving a complex problem, rather than learning to express a solution without ambiguity. A number of programming languages are covered in the course so there is a lot of new syntax, however, the focus is on breaking down problems using abstraction and top-down design. Each language provides its own abstractions and this provides additional vocabulary and shapes the thought process that is useful even in languages not taught in the course.

Atomic, molecular and laser physics is one of the most actively researched field in Physics. This course provides a modern introduction to the physics of atoms. It will cover classical topics like energy structure of Hydrogen atom, its fine and hyperfine structure and modification of this structure in the presence of static fields. This would be followed by classical and semi-classical treatments of light-atom interactions. The course will introduce the basics of ultra-cold atoms, how are they produce and how can they be utilized. Regimes of isolated cold atoms as well as complex atomic states will be discussed. The course will conclude with a brief introduction to the quantum mechanical treatment of molecular structure and molecular spectroscopy.

This core course overviews chemical thermodynamics with focus on the Zeroth, First, Second and Third laws of thermodynamics and how it relates to the equilibrium properties of macroscopic systems. Relations between the state functions that dictate the direction and extent of physical and/or chemical changes are discussed. Calculations involving work, heat, internal energy, heat capacities, enthalpy and entropy are discussed for various processes. Phase diagrams are for single-component systems are discussed using Clausius-Clapeyron equation. The second part of the course introduces quantum mechanics and solution of Schrodinger equation for simple systems. It discusses wave functions, radial

distribution functions, operators and eigenvalues, and how the position, momentum and energy of a particle are related with them in quantum mechanics. Periodic properties of elements are discussed in light of the electron-electron repulsion terms, radial distribution functions, the most probable radii, shielding and penetration, and the energies of orbitals.

Condensed matter is by far the largest single subfield of Physics. The lack of publicity of the field would suggest otherwise. The scope of condensed matter physics is immense from explaining why metals are shiny to why glass is transparent to why rubber is soft. It almost covers almost all the physical world around us. Yet the structure of the field can be summed up in a few fundamental concepts and this course would try to explore them. The structure of the theory is non-reductionist i. e. that the macroscopic results emerging from the theory can be very different than the behavior of the individual microscopic states. So be ready for some surprises as the course progresses. For those of you, who have taken quantum and statistical physics, this course would be a playground to put those concepts to tests.

Atomic, molecular and laser physics is one of the most actively researched field in Physics. This course provides a modern introduction to the physics of atoms. It will cover classical topics like energy structure of Hydrogen atom, its fine and hyperfine structure and modification of this structure in the presence of static fields. This would be followed by classical and semi-classical treatments of light-atom interactions. The course will introduce the basics of ultra-cold atoms, how are they produce and how can they be utilized. Regimes of isolated cold atoms as well as complex atomic states will be discussed. The course will conclude with a brief introduction to the quantum mechanical treatment of molecular structure and molecular spectroscopy.

Advanced Reaction Engineering

This course has been designed as an introduction to general topology. The student enrolled in this course should have a back-ground in Set Theory (and preferably some knowledge of Real Analysis - I). This course covers basic point set topology, in particular, Metric and Topological spaces, Separation Axioms, Connectedness, Compactness, Product spaces and Quotient topology. We will, also cover some algebraic topology, i.e. fundamental groups of topological spaces.

Partial Differential Equations (PDEs) permeate various scientific disciplines. This course deals with: Terminology; boundary and initial value problems; well- and ill-posed problems. the Laplace, wave and diffusion equations; the Klein-Gordon equation; Method of characteristics, separation of variables, integral transforms, Green's functions; potential scattering; dispersion and diffusion; regular and singular perturbation theory; asymptotes for complete solutions; Nonlinear PDEs: Converting nonlinear equations into linear PDEs; some exactly solvable cases; dimensional analysis and similarity; traveling waves; nonlinear diffusion and dispersion; the KdV, nonlinear Schrödinger and Sine-Gordon equations; reaction-diffusion equations; Fisher's equation; singular perturbations: boundary layers, homogenization. Variational Methods. Free-boundary value problems.

### B

Biochemical engineering is the application of chemical engineering to biological systems. Biological systems are complex. They obey the rules of chemistry and physics and are susceptible to engineering analysis. Biochemical engineers use living cells on commercial scales in the biotechnology, food, and pharmaceutical industries, for several purposes such as to develop new medicines, semisynthetic organs, and nutritious foods, and to degrade pollutants. As a biochemical engineer you would engineer and operate systems that contain living cells and biomolecules, design and operate bioprocesses to manufacture biomolecules and drugs, and apply biological principles to the engineering of living cells. This course will give you the foundational knowledge of biochemical engineering which will opens doors for pursuing careers or graduate studies in biotechnology, bioengineering and the pharmaceutical industry. We will cover enzyme technology; design of bioreactors and microbial fermentations; separations of biological products; microorganisms in chemical and biochemical syntheses. These will include concepts of heat and mass transfer, as well as the application of quantitative engineering principles to the analysis of biological processes, including thermodynamics, kinetics and stoichiometry. We also aim to cover cell culture and cellular engineering including genetic manipulation of cells by classical and recombinant DNA techniques.

The Biochemistry sophomore course is designed to provide undergraduate students an understanding of fundamental concepts in Biochemistry. Students will learn molecular mechanisms underlying biological processes, fundamental principles that drive biochemical reactions, molecular organization starting with themonomeric subunits, structures and how structure relates to function, different techniques in studying structural properties and finally the metabolic pathways of biological system.

### C

This course deals primarily with the equilibrium properties of macroscopic systems. Four thermodynamics laws are discussed and calculations involving work, heat, internal energy, heat capacities, enthalpy, entropy, the Gibbs function and chemical potentials are performed. Fundamental thermodynamic equations and Maxwell relations are discussed. It also covers phase equilibria of single and two component systems, ClausiusClapeyron equation, ideal/non-ideal solutions, colligative properties. It includes discussions on chemical equilibria of reactions in gas and solution phases and effects of temperature and pressure on equilibrium compositions. Statistical thermodynamics is also introduced in the last few lectures.

Chemical process simulation course is designed to challenge chemical engineers to combine basic engineering knowledge and tools for process simulation to solve engineering problems. This course will cover the use of a software package to model chemical processes and unit operations in stand-alone and combination modes. Processes to model on both continuous and batch modes include, heating/cooling, heat exchange, fluid flow, phase equilibria, flash operations, distillation, absorption/desorption, extraction, and chemical reactions. This course aims to develop and improve additional transferable skills like problem-solving, independent & cooperative learning, project management, and technical documentation.

This course is intended as a medium-level introduction to computational methods and computer programming for science and engineering students. The course will introduce basic programming concepts like data structures, iteration, recursion, abstraction, and branching. Introductory tutorials on Python will be arranged to implement these concepts using Python. We will then cover basic algorithms for searching, sorting, optimization, and stochastic approaches. The basic ideas of algorithm complexity and the techniques to design efficient algorithms will be developed all along. The course will have selective applications of these ideas in solving problems in modern physics. In this course, the students will be required to write codes in the Homeworks using Python.

The course will be suitable for junior and senior SSE students with a background in mechanics (PHY101) and modern physics (PHY2104). Previous experience in programming in any language will be very helpful, though not necessarily needed. However, students must learn programming using Python in this course. We will have a few introductory tutorials on Python and students are expected to learn the syntax on their own during the later course as we will concentrate on algorithms, program complexity, and problem solutions in the lectures rather than the nitty-gritty of Python itself.

This course deals with the analysis on data and design of equipment in which reactions occur. This course will cover the fundamental aspects of kinetics, data acquisition, heat and mass transfer for each type of reactor and residence time distributions. Thermal effects: exothermic and endothermic reactions. The course will also make students aware multiplicity and to reactor dynamics and chemical instabilities along with the needs and opportunities for chemical reaction engineering in industry.

This course provides introduction to computational biology and the tools and techniques used in the analyses of genomic and proteomics data. The emphasis is on the fundamentals of nucleic acid and protein sequence analysis, structural analysis, and phylogenetic analysis. A significant amount of time is spent for hands-on training and programming of topics covered in the lectures.

This course focuses on theory, algorithms and applications of convex optimization. Convex optimization deals with optimization problems where

the objective function and the constraints of the problem are both convex. These problems appear in a variety of applications in diverse fields of

science and engineering (e.g., statistics, signal/image processing, wireless communications, medical imaging, machine learning, economics, to

name a few).

Students will be trained to recognize, model/formulate, and solve convex optimization problems. Applications will revolve around medical imaging,

big data and machine learning, and statistical (parameter) estimation. The course lectures will be divided into 4 sections: (1) Basics of convex

analysis, (2) First-order methods, (3) Duality, and (4) Second-order methods. For advanced topics, we will cover selected problems covering the

research themes of the class. Implementation of optimization algorithms will be carried out in MATLAB.

Pedagogical approach: We will develop a strong motivation to study these tools using applications (and examples) from high-school, college, and

undergraduate mathematics and physics followed by learning of high-level concepts and algorithms using intuition and reasoning.

Cells in multicellular organism communicate with each other and internally by a complex network of signaling pathways that regulate cellular processes such as growth, differentiation, migration, survival and apoptosis. This course aims to provide comprehensive understanding of different signaling components and pathways involved in such processes and how deregulation of key signaling proteins involved in these pathways leads to human diseases such as cancer. There will be two lectures every week followed by a session of recitations where students will discuss a paper relevant to the topic studied during the week. Assignment at the end of the course will consist of research paper of choice to be presented to the class.

Condensed matter is by far the largest single subfield of Physics. The lack of publicity of the field would suggest otherwise. The scope of condensed matter physics is immense from explaining why metals are shiny to why glass is transparent to why rubber is soft. It almost covers almost all the physical world around us. Yet the structure of the field can be summed up in a few fundamental concepts and this course would try to explore them. The structure of the theory is non-reductionist i. e. that the macroscopic results emerging from the theory can be very different than the behavior of the individual microscopic states. So be ready for some surprises as the course progresses. For those of you, who have taken quantum and statistical physics, this course would be a playground to put those concepts to tests.

This course introduces process dynamics by mathematical modeling, analysis, design and tuning of feedback / feedforward controllers in context of various control strategies used in chemical process industries. The design and analysis are mostly for linear systems and connection to nonlinear systems is made by introducing the concept of linearization around a chosen operating point. Students will perform a computer-simulation-based design project to relate the learned mathematical concepts to real world processes and also to learn team-based problem solving.

This is the first course of a two semester course sequence. This course covers limits, continuity, differentiation and its applications, integrals and techniques of integration, applications of integrals, early transcendental functions.

This is a second course in Electrical Circuit Theory. This course covers various aspects of electrical networks. The focus is on the description and analysis of electrical circuits in transform domain. Transform domain here refers to Laplace domain and Phasor domain. Transform domain description and analysis of electrical networks enables students to learn and recognize the importance of poles, zeros and to determine the stability of electrical circuits. Two port network descriptions in terms of z, y, h, and transmission parameters are also included. Sinusoidal steady state circuit analysis along with various frequency response plots such as magnitude plots, phase plots, polar plots, Bode plots etc. are covered to give the students a complete picture of various circuit analysis tools in transform domain. Furthermore, power analysis, concepts of active and reactive power, power factor and power factor correction are also covered.

The first course in the Systems series helps students understand the basic operation of computing hardware, how to evaluate its performance, and how the hardware interfaces to software. When designing or selecting a computer system, it is important to understand the tradeoff among various components and operational blocks. This course will cover the basic concepts of Computer Organization including the design of single-cycle and multi-cycle CPU control and datapath, memory systems including hierarchy, caching and virtual memory, and input/output subsystems. Instruction set architecture of a RISC processor is studied. Some aspects of pipelining and parallel processing are also covered.

The Labs will have focus on learning and experimenting with MIPS Assembly Level Programming.

This is the second of a two-semester Calculus sequence. This course covers, Sequences and Series, Vectors, Partial Derivatives and Linear Approximations, Maxima and Minima for functions of several variables, Multiple Integrals, Vector Calculus, Green’s, Gauss’ and Stokes’ theorem

Chemical engineering thermodynamics forms the foundation for understanding chemical engineering processes. This course teaches concepts of thermodynamics with emphasis on application to chemical systems. Students will learn how to formulate and solve engineering problems involving phase/reaction equilibrium and energy flow. Advanced topics such as thermodynamics of electrolyte solution, adsorption and separation will also be covered. The attained knowledge will help the students to model existing industrial processes as well as analyzing novel solutions in research and technology development.

This course provides introduction to computational biology and the tools and techniques used in the analyses of genomic and proteomics data. The emphasis is on the fundamentals of nucleic acid and protein sequence analysis, structural analysis, and phylogenetic analysis. A significant amount of time is spent for hands-on training and programming of topics covered in the lectures.

The first course in the Systems series helps students understand the basic operation of computing hardware, how to evaluate its performance, and how the hardware interfaces to software. When designing or selecting a computer system, it is important to understand the tradeoff among various components and operational blocks. This course will cover the basic concepts of Computer Organization including the design of single-cycle and multi-cycle CPU control and datapath, memory systems including hierarchy, caching and virtual memory, and input/output subsystems. Instruction set architecture of a RISC processor is studied. Some aspects of pipelining and parallel processing are also covered.

The Labs will have focus on learning and experimenting with MIPS Assembly Level Programming.

This course is intended as a medium-level introduction to computational methods and computer programming for science and engineering students. The course will introduce basic programming concepts like data structures, iteration, recursion, abstraction, and branching. Introductory tutorials on Python will be arranged to implement these concepts using Python. We will then cover basic algorithms for searching, sorting, optimization, and stochastic approaches. The basic ideas of algorithm complexity and the techniques to design efficient algorithms will be developed all along. The course will have selective applications of these ideas in solving problems in modern physics. In this course, the students will be required to write codes in the Homeworks using Python.

The course will be suitable for junior and senior SSE students with a background in mechanics (PHY101) and modern physics (PHY2104). Previous experience in programming in any language will be very helpful, though not necessarily needed. However, students must learn programming using Python in this course. We will have a few introductory tutorials on Python and students are expected to learn the syntax on their own during the later course as we will concentrate on algorithms, program complexity, and problem solutions in the lectures rather than the nitty-gritty of Python itself.

### D

Developmental Biology is an extremely vast subject which deals with the processes and mechanisms that lead to development of an adult organism from a fertilized egg. This course will introduce students to basic concepts in development and principles that lead to development of multicellular eukaryotes. Both vertebrate and invertebrate models will be discussed with special emphasis on Drosophila where process of development is understood at mechanistic level in much more detail. In particular, emphasis will be on the genetic and epigenetic basis of development including stem cells, reprogramming of cells and process of regeneration in eukaryotes. Students will be regularly given research literature published in the field of development to understand how they can experimentally approach different topics of development. Every week students will critically discuss research papers related to ongoing lectures and lead a discussion in class. The review and discussion of research material will enable students to formulate an experimental question and hypothesis to address and design experiments to test the hypothesis.

Deep Learning is a hierarchical learning methodology based on artificial neural networks which are algorithms inspired by the structure and function of the brain. It has applications in wide-range of industries these days such as face-recognisers working at massive scales, robotics, speech translation, text analysis, improving customer experience, autonomous vehicles etc.

In this course we will take a “hands-on approach” and start will implementation of basic building blocks such as training a simple perceptron and move to design and train a deep convolution neural network. Course will concentrate in developing both mathematical knowledge and implementation capabilities. The implementations will be python based using TensorFlow and Keras. After establishing our foundation in convolutional neural networks we will start looking into applications of deep learning in both spatial as well as time-series data and explore various network architectures suited for each. The objective is to help you build a career in AI and Machine learning, to make you comfortable enough that you can understand various learning problems and develop your own deep learning based solutions.

Data structures are abstractions for storing data in a computer system and form an essential building block in the design of efficient algorithms. The knowledge of data structures plays a central role in computer science and engineering and is highly sought-after in the technology industry. They are used in a wide variety of applications today including search engines (e.g., Google, Bing), social networking applications (e.g., Facebook, Twitter), embedded systems (e.g., cell phones, robots), and DNA analysis. This course introduces the fundamentals of data structures and aims to provide a deep understanding of how to systematically organize data in a computer system.

The students will be introduced to analytical tools for comparing different data structures in terms of their time and space complexity. Finally, the course will augment student’s theoretical understanding of data structures with rigorous programming assignments, which form an essential component of the course. Main topics include: Abstract data types; Asymptotic notation and analysis tools; Lists; Stacks; Queues; Recursion; Trees (general, game, etc); Binary trees; Binary search trees; AVL trees; Huffman coding; B-trees; Multi-way trees; Hashing; Dictionaries; Priority queues; Heaps; Sorting (Heapsort, insertion sort, merge sort, quicksort, etc.); Searching; Tries; Graphs; Depth-first search; Breadth-first search; Shortest path algorithms; Minimum spanning trees; Advanced topics.""Data structures are abstractions for storing data in a computer system and form an essential building block in the design of efficient algorithms. The knowledge of data structures plays a central role in computer science and engineering and is highly sought-after in the technology industry. They are used in a wide variety of applications today including search engines (e.g., Google, Bing), social networking applications (e.g., Facebook, Twitter), embedded systems (e.g., cell phones, robots), and DNA analysis. This course introduces the fundamentals of data structures and aims to provide a deep understanding of how to systematically organize data in a computer system.

Deep Learning is a hierarchical learning methodology based on artificial neural networks which are algorithms inspired by the structure and function of the brain. It has applications in wide-range of industries these days such as face-recognisers working at massive scales, robotics, speech translation, text analysis, improving customer experience, autonomous vehicles etc.

In this course we will take a “hands-on approach” and start will implementation of basic building blocks such as training a simple perceptron and move to design and train a deep convolution neural network. Course will concentrate in developing both mathematical knowledge and implementation capabilities. The implementations will be python based using TensorFlow and Keras. After establishing our foundation in convolutional neural networks we will start looking into applications of deep learning in both spatial as well as time-series data and explore various network architectures suited for each. The objective is to help you build a career in AI and Machine learning, to make you comfortable enough that you can understand various learning problems and develop your own deep learning based solutions.

This course focuses on the principles and practices of Digital Logic Circuit Design and is a first course in this area. Topics covered include: Boolean Algebra, Number Systems, Logic Gates, Logic Technologies, DRAM, SRAM, ROM, Inverters, Circuit Implementation of Logic Gates, Speed of Logic Gates and Operating Frequencies, Logic implementation of Boolean expressions, Karnaugh Maps, Analysis and Design of Combinational Logic Circuits, Analysis and Design of Sequential Logic Circuits, Circuits for Arithmetic Calculations, Circuits using memories and Flip-Flops, Registers and Register files, State-Machines, Memory Systems, Basic Processor and Control Unit Design.

This is a research topics course in Computer and network Security

• Biased by interests of the faculty

• Fairly wide coverage of topics

• Course project

The project will be graded on the following:

(a) Complexity and the amount of the work carried out.

(b) Your understanding of the subject of the report.

(c) Organization and writing.

(d) Comprehensiveness of the survey, originality of the ideas in experimental projects.

Grading emphasis may change based on the nature of the report: survey or experimentation or measurement or implementation.

### E

This course extends the concepts of static electric and magnetic fields to time-varying fields that give rise to electromagnetic waves. Maxwell’s equations are presented as mathematical description of laws governing these waves. Propagation of electromagnetic waves through different types of media and their behavior at interfaces is explored. Potential fields are introduced along with a discussion on Gauge transformations. The phenomenon of radiation with emphasis on dipole radiation will be studied. Finally, the connection between special theory of relativity and electrodynamics is explored.

This course introduces the fundamentals of DC and AC electromechanical systems to be used for variety of applications. The course starts with the study of fundamental physical laws of electrical devices and appropriate mathematical models are developed to understand their operation and design. The physical construction, operation and mathematical design of transformers, DC machines, and AC machines will be discussed in detail. The speed control of rotating machines will also be introduced.

Developmental Biology is an extremely vast subject which deals with the processes and mechanisms that lead to development of an adult organism from a fertilized egg. This course will introduce students to basic concepts in development and principles that lead to development of multicellular eukaryotes. Both vertebrate and invertebrate models will be discussed with special emphasis on Drosophila where process of development is understood at mechanistic level in much more detail. In particular, emphasis will be on the genetic and epigenetic basis of development including stem cells, reprogramming of cells and process of regeneration in eukaryotes. Students will be regularly given research literature published in the field of development to understand how they can experimentally approach different topics of development. Every week students will critically discuss research papers related to ongoing lectures and lead a discussion in class. The review and discussion of research material will enable students to formulate an experimental question and hypothesis to address and design experiments to test the hypothesis.

This is an introductory course in the field of electrical power systems covering the core areas of generation, transmission and distribution. Power systems are complex interaction of these areas and students of this course would study the operation of interconnected power systems. Electrical energy is one of the most convenient forms of energy and is used in many different applications requiring a wide range of power. This course will cover the fundamental concepts in planning and operation of modern electric power systems. Topics to be covered include Power system structure and operation, poly-phase circuits and their application in three-phase transformers, modeling of components such as transmission lines, transformers, generating plants and loads, and power flow analysis.

This course is designed to teach students about the structure of the Pakistani Power Sector, the regulatory institutions that oversee the

industry, and the new market institutions that are being envisaged for Pakistan through the restructuring of the Industry. This course would

introduce the basics of power systems operation, transition to smarts with changing load dynamics as well as variable renewable generation.

The course will also introduce basics of market economics, macroeconomic principles and concepts of dispatch in power systems context. We

will also cover in significant detail the new market structure for Pakistan based on competitive trading bilateral contracts along with

introduction of market contracts envisioned for new procurement.

The course also includes a research project in which students would be required to include technical and market concepts related to various

institution within the power sector.

This laboratory course is designed to experimentally demonstrate chemical synthesis techniques/methodologies practicing safety rules and guidelines, and perform data analysis. Students will perform laboratory experiments carefully selected from a range of physical chemistry, inorganic/analytical chemistry and organic chemistry topics. Students will also be introduced to literature-searching techniques, error analysis and

report writing.

Embedded Systems is a major class of computing systems that covers a wide spectrum of devices ranging from communications such as PDA, smartphones to avionics and automobiles to household electronic appliances such as smart ACs microwave ovens and refrigerators. In this course, we will get familiarized with the issues and challenges faced by real-time embedded systems and their future evolution trends.

### F

Transport phenomena comprise three topics: fluid dynamics, mass transfer and heat transfer. Fluid dynamics involves the transport of momentum, mass transfer is concerned with the transport of mass of various chemical species and heat transfer deals with the transport of energy. This course is designed to study and analyze transport of momentum and provides the students with a basic understanding of fluid properties, fluid statics and fluid flow. Some of the topics include the mathematical description of fluid flow in terms of Lagrangian and Eulerian coordinates; the derivation of the Bernoulli’s equation and the Navier-Stokes equations from the fundamental principles of mass and momentum conservation; use of dimensional analysis to identify important non-dimensional parameters that describe any given flow problem; and analytic solutions of the Navier-Stokes equation. The knowledge of fluid dynamics gained in this course is a foundation for many other courses in the Chemical Engineering degree program as well as other disciplines, such as renewable energy, atmospheric and oceanic circulation, and biological processes such as the flow of blood.

### G

This course has been designed as an introduction to general topology. The student enrolled in this course should have a background in Set Theory (and preferably some knowledge of Real Analysis - I). This course covers basic point set topology, in particular, Metric and Topological spaces, Separation Axioms, Connectedness, Compactness, Product spaces and Quotient topology. We will, also cover some algebraic topology, i.e. fundamental groups of topological spaces.

This course will expose students to a wealth of information available to us in the post-genomic era which can be exploited to understand cellular function in greater details. It will start with a quick overview of important fundamentals followed by landmark discoveries which had left an impact in the field of genetics and genomics. In particular, genetics and epigenetics of development and gene regulation and how both are linked will be covered in detail. Moreover, emphasis will be on learning building a scientific question and how it can be addressed using modern molecular and genomic approaches will be covered. Finally, students will be exposed to computational approaches to understand functional genomics and how it can enhance our understanding of cellular function.

The course is an introduction to general relativity. We start with a geometrical description of special relativity and the structure of Minkowski spacetime. The course also covers basic ideas of tensor algebra and differential geometry. Then we introduce Einstein's field equations that relate the geometry of the spacetime with the matter. We go on to solve the equations in some simple cases.

### H

This course offers a thorough introduction into both the underlying theories of human-computer interaction and the practical application of these insights. This course will equip students with tools and techniques required to design user-friendly interactive systems. This is not a programming-intensive course but students are expected to develop working prototypes.

The point of departure for this course is the design of everyday things. It will be shown that the principles underlying the design of such artifacts also apply to the design of the digital media/interactive systems/software. It will then be shown how concepts such as usability and utility may be defined and operationalized, and how the user centered design process may contribute to the achievement of optimal results from a usability and utility perspective. After this, the user interface development process also known as User-centered design (UCD) process will be discussed in detail. The group project is the focal point of this course and will be based on the UCD process.

### I

This is a beginners-level course that focuses on the foundational technologies behind blockchain. We will cover the concepts of distributed ledger, consensus mechanisms, authentication techniques, and relevant protocols. The course will provide case studies of blockchain applications such as cryptocurrencies, supply chain management, and B2B/B2C/C2C scenarios. The course will also provide hands-on experience with building and deploying smart contracts.

Game Theory is the study of strategic situations i.e. where the outcome for individuals depends on their own actions as well as the actions of others. As such it has a wide range of applications in many fields including Economics, Political Science, Law and Sports. This course introduces the fundamental principles, techniques and notation of Game Theory as well as some basic insights provided by some well-known games.

This course provides a conceptual and practical introduction to programming. The focus is on programming rather than the particular choice of programming language, with general principles being brought out through the study of ‘C++’. This course will equip students with tools and techniques to implement a given problem programmatically. Main topics include: advanced data types; Structures; Classes; Objects; Streams; Friend functions; Overloaded operators; Recursion; Namespaces; Pointers and References to objects; Linked lists; Queues; Stacks; Trees (General, game, binary); Inheritance; Polymorphism; Exceptions; Templates; Basic Design Patterns.

This laboratory course aims to develop skills for the synthesis and characterization of inorganic compounds and materials. Additionally, qualitative and quantitative analysis of some inorganic ions is included. Development of various experimental skills for instance, handling of air/moisture sensitive reactions, use of high temperature furnaces, running homogeneous catalytic reactions, use and interpretation of uv-vis, NMR and X-ray Powder Diffraction (PXRD) will be targeted. Students will synthesize and characterize main group/transition metal compounds including those relevant to bioinorganic and nanochemistry. Metal complexes with various ligands will be synthesized to evaluate the ligand field strengths. At least one organometallic catalyst will be prepared and its use in organic synthesis/catalysis will also be demonstrated.

This course has two parts. The first deals with the basics of quantum computing. We will learn how to perform computations using simple quantum operations, called quantum gates. We will also build basic algorithms to show that quantum computers are faster than classical computers in solving some problems. The second part deals with quantum information that generalizes concepts from classical information theory. Using quantum information theory, we will then be able to understand quantum cryptography and noisy quantum processes. This will help us understand the limitations of current quantum computers due to noise. During the course, we will also spend some time on the physics of implementing single and two-qubit quantum gates.

This course focuses on a new emerging topic the Internet of Things (IoT). IoT enables people to remotely interact with their "things". It‘s going to make everything in our lives "smart" - from alarm clock to doorbell to home to street lights to airports. IoT is the wildest extension of the Internet mankind has ever seen with multiple surveys reporting over 50 billion "things" to be added to the Internet by 2025. This extension brings with itself enormous CS research challenges that we will discuss in this course. The course includes a small amount of background 'primer' review material to get all students to an equivalent level, but primarily lectures will follow a "seminar style" structure. This implies course work includes readings, presentations, and discussion of technical papers taken from the currently available IoT literature. Seminar style requires active student participation in both the presentations and in the discussions. This participation is a significant component in the students' grade.

The Immune System is an intricate network of cells tissues and organs that works in sync to protect the organism from pathogens. Through a series of steps known as immune responses, the immune system attacks invaders and foreign substances that enter the body. The remarkable diversity of immune system allows it to detect and eliminate variety of pathogens such as viruses, bacteria, parasites and fungi. Surveillance and memory are two important functions of immune system which In addition to attacking pathogens entering the body, immune systems also keeps a record (memory) of each pathogen that infects the host, so as to handle it better the next time. The course will start with the study of cells and basic components of the two branches of immune systems namely innate and adaptive. Later half of the course will deal with more complex concept, which include initiating and sustaining the immune response. Third section will focus on the diversity of immune responses and the molecular and cellular basis of diversity. Overall the course will cover cells and tissues of the immune system, lymphocyte development, the structure and function of antigen receptors, the cell biology of antigen processing and presentation, including molecular structure and assembly of MHC molecules, the biology of cytokines, leukocyte-endothelial interactions, and the pathogenesis of immunologically mediated diseases. The course is structured as a series of lectures and tutorials in which will provide in-depth information on each topic. Classes are designed to be highly interactive where students will be encouraged to engage in discussions with fellow classmates and with the instructors.

This is a beginners-level course that focuses on the foundational technologies behind blockchain. We will cover the concepts of distributed ledger, consensus mechanisms, authentication techniques, and relevant protocols. The course will provide case studies of blockchain applications such as cryptocurrencies, supply chain management, and B2B/B2C/C2C scenarios. The course will also provide hands-on experience with building and deploying smart contracts.

This course covers advance topics from artificial intelligence (AI), and knowledge management/engineering domain. The course starts with an overview of knowledge management principles, knowledge engineering essentials, and then links it to knowledge based systems. The post midterm course covers topics related evolutionary algorithms, statistical learning and multi-agent systems. The interconnections of these topics with the knowledge management systems are established. The topics covered in the course are integrated through a semester long project that runs in parallel to the course.

Introductory biology aims to provide a broad overview of biology as it stands today, exposing students to a variety of topics in modern molecular and cellular biology. The course is divided into four modules:

1. Macromolecules and Cell Biology:

We start with an introduction to the molecules of life and how they are organized into a cell, the basic unit of life in all living organisms. Students learn how cells communicate with each other, how they divide, and how they produce and consume energy.

2. Genes and Development

The course then focuses on the organization of genetic material and how various molecular, genetic and biochemical processes underlie the functioning of cells from replicating their genetic material for cell division to accurately producing essential proteins during development.

3. Omics and Systems Biology:

This module provides an overview of how modern biology is reliant on generation and analysis of big data and how this data can be utilized for a better understanding of biological systems.

4. Human Diseases and Drug Discovery:

In the end, we discuss how communicable and non-communicable human diseases are caused and how understanding the molecular mechanisms of these diseases allows us to develop more effective drugs. Manipulating genetic materials is at the heart of advances in life sciences that we see today from biomedical to agricultural sciences. This module also provides an overview of how the genetic makeup of organisms can be manipulated in the laboratory.

This is the first course towards the understanding of machine intelligence. It introduces basics of learning and search algorithms.

This is not an exhaustive coverage of quantum field theory. Rather it is a first introduction for the motivated physics student to understand and appreciate the basics of one of physics’s most powerful and far-reaching machinery to understand the natural world. The concepts will be physically motivated and addressed in the formal mathematical descriptions. By the end of this course, students will be able to take more extensive treatments of the subject or initiate, through self-study, the reading of more advanced texts.

Advances in Information and Communication Technologies (ICTs) have had a transformative impact on the developed world but does it have the potential for a similar impact in the Global South? This course will provide an introduction to the growing field of ICTD (Information and Communication Technologies for Development). The goal of is to provide background to develop and deploy technologies in a global setting that address development challenges. The course will cover health information systems, data collection techniques, applications for basic mobile phones, user interface design for low literate populations, behaviour change communication, voice based social networks, AI for social good and mobile financial services

This course will serve as a bridge between calculus and further analysis. In this course we will cover fundamental concepts such as limit, continuity, and differentiation but with much more rigor than it is done in basic calculus courses.

### J

Junior Design Studio - Electric Vehicles

### L

This is the first course of a two semesters sequence in linear algebra. This course gives a working knowledge of: systems of linear equations, matrix algebra, determinants, eigenvectors and eigenvalues, finite-dimensional vector spaces, matrix representations of linear transformations, matrix diagonalization, changes of basis, Separable and first-order linear equations with applications, 2nd order linear equations with constant coefficients, method of undetermined coefficients, Systems of linear ODE's with constant coefficients, Solution by eigenvalue/eigenvectors, Non homogeneous linear systems.

### M

This course emphasizes the mathematical skills used by engineers and demonstrates their applicability through context-rich engineering examples. Aims of the course include increasing confidence and facility in solving engineering problems using mathematics, developing better judgment in selecting the mathematical tools, and methods. It features the mathematical foundations on which some of the world’s engineering advancements have rested on, or are related to. Topics include, solution of ordinary differential equations, initial and boundary value problems, numerical solution of ordinary differential equations and series solutions.

This is a core course in the area of microelectronic circuits. It teaches essential techniques required to design, analyze and simulate modern analog and digital circuits for wide variety of applications. The topics covered include fundamental building blocks of circuits such as operational amplifiers, cascode stages and current mirrors, differential amplifiers. The concepts of frequency response, feedback and stability in circuits are covered. Oscillators, and phase locked loop circuits are explored. The use of SPICE tools in the design, simulation, synthesis and implementation is explored.

This course is intended to be a first introduction to quantum phenomena in nature. Quantum Mechanics forms the basis of our description of nature at small scales and a clear understanding of it is required to understand phenomena ranging from atoms and chemical bonding to semiconductors and nuclear physics. We will present a concise and comprehensive picture of quantum theory with emphasis on concept building. The concepts will be organized around the idea of wave particle duality and its consequences. Numerous applications to real world phenomena will be discussed throughout the course. The course also has a component that discusses the application of statistical ideas in physics and how it gives rise to our common understanding of phenomena involving heat and temperature in the form of laws of thermodynamics including their applications.

Fundamental concepts in atomic and molecular structures of different classes of materials and how they can be tuned by processing and other treatments. The thermal, electrical, magnetic and optical properties will be discussed for metals, alloys, polymers, ceramics, composites and advanced materials. Moreover, the effect of processing conditions on the physical properties of materials will be discussed along with their implications in materials design. Nanomaterials synthesis, properties, and their modern applications and potential will also be briefly discussed.

Mathematical methods I is a BS Physics core course that presents a wide variety of mathematical methods, tools and concepts which are used in science and engineering. The main objective of this course is to provide students with a repertoire of mathematical methods that are essential to the solutions of advanced problems encountered in the fields of applied physics and engineering. In this course we will discuss Vector calculus, Complex analysis, Fourier series, integral transforms (including Fourier and Laplace), special functions and ordinary as well as partial differential equations. Topics are covered in detail, where possible, we will attempt to link the mathematical tools such as Matlab and Mathematica that we will discuss with physical problems to provide context and help develop understanding. Problem solving is emphasized and encouraged through graded assignments.

This course introduces the basic principles of machine learning that includes the understanding of learning algorithms in supervised and unsupervised settings. The main focus of the course will be the study of predictive modeling techniques. Besides, we’ll pay special attention to topic modeling as well as inference and learning in graphical models.

Membrane Science and Engineering

This course introduces the basic principles of machine learning that includes the understanding of learning algorithms in supervised and unsupervised settings. The main focus of the course will be the study of predictive modeling techniques. Besides,

we’ll pay special attention to topic modeling as well as inference and learning in graphical models.

Determining the structure of organic compounds by using spectroscopic techniques is an important part of the modern day research and

development. This course is designed to enable the students to understand the concepts of spectroscopy-based techniques. These concepts will

then be applied to solve problems related to the structure elucidation of organic compounds. We will discuss theories and principles underlying

the development of modern spectroscopic techniques and then focus on the application in determining the structure of organic compounds.

### N

The main goal of this course is to provide an early introduction to core concepts in computer networks and distributed system and to understand emerging technologies in the net-centric computing area and assess their current capabilities, limitations, and near-term potential. An important goal of the course is to provide hands-on experience with substantial programming assignments.

1. We will be covering a broad range of topics in order to understand the basic issues, concepts, principles, and mechanisms in networks and distributed systems.

2. We will focus on issues encountered in building Internet and web systems: topics includes network applications, protocols and standards, scalability, interoperability (of data and code), atomicity and consistency models, replication, and location of resources, services, and data.

3. What is the "cloud"? How do we build software systems and components that scale to millions of users and petabytes of data, and are "always available"?

4. In the modern Internet, virtually all large Web services run on top of multiple geographically distributed data centers: Google, Yahoo, Facebook, iTunes, Amazon, eBay, Bing, etc.

5. Services must scale across thousands of machines, tolerate faults, and support thousands of concurrent requests.

6. This course, aimed at a sophomore with exposure to basic programming within the context of a single machine, the later half of the course will focus on the issues and programming models related to such cloud and distributed data processing technologies: data partitioning, storage schemes, and parallel algorithms.

The format will be two 1hour 15 min lectures per week, plus assigned readings. There will be regular homework assignments, plus a midterm and a final exam.

The main goal of this course is to provide an early introduction to core concepts in computer networks and distributed system and to understand emerging technologies in the net-centric computing area and assess their current capabilities, limitations, and near-term potential. An important goal of the course is to provide hands-on experience with substantial programming assignments.

1. We will be covering a broad range of topics in order to understand the basic issues, concepts, principles, and mechanisms in networks and distributed systems

2. We will focus on issues encountered in building Internet and web systems: topics includes network applications, protocols and standards, scalability, interoperability (of data and code), atomicity and consistency models, replication, and location of resources, services, and data.

3. What is the "cloud"? How do we build software systems and components that scale to millions of users and petabytes of data, and are "always available"?

4. In the modern Internet, virtually all large Web services run on top of multiple geographically distributed data centers: Google, Yahoo, Facebook, iTunes, Amazon, eBay, Bing, etc.

5. Services must scale across thousands of machines, tolerate faults, and support thousands of concurrent requests.

6. This course, aimed at a sophomore with exposure to basic programming within the context of a single machine, the later half of the course will focus on the issues and programming models related to such cloud and distributed data processing technologies: data partitioning, storage schemes, and parallel algorithms.

The format will be two 1hour 15 min lectures per week, plus assigned readings. There will be regular homework assignments, plus a midterm and a final exam.

### O

Introduction to ODEs, Power Series Method, Eigen value problems and Sturm-Liouville equations, special functions: Hyper geometric equation, Bessel’s equation, Legendre’s equation, Systems of ordinary differential equations, Well-posed initial value problem (i.e. existence, uniqueness, continuation and continuous dependence); Special linear systems, Applications. Laplace Transform Method for ODEs (If time available).

The main focus will be on organo-transition metal chemistry and catalysis. The following topics will be covered: Structure, bonding, synthesis, and characterization of organo-transition metal compounds, Reaction mechanisms, Ligand substitution reactions, oxidative addition and reductive elimination, insertion and elimination reactions, nucleophilic and electrophilic addition and abstraction, Carbenes, metathesis and polymerization, homogenous catalysis, activation of small molecules, heterogeneous catalysis. The applications of organo-transition metal chemistry in organic synthesis & industry will be highlighted. In addition, time permitting, brief introduction to the following topics: Green chemistry, Cluster and cage compounds, Biocoordination chemistry.

Spectroscopic techniques have attained important role the modern day chemistry in determining the structure of the organic compounds. This course is designed to introduce the theory of these spectroscopic techniques and then focus on the application of these techniques in solving the problems related to structure elucidation of the organic compounds.

### P

This course teaches the fundamental physics and the design of conventional and advanced photovoltaic devices or solar cells. The focus is on the in-depth understanding of the physical mechanisms and the material properties that are necessary for modeling,

analyzing, and designing of current and next generation solar cells technologies. There will be an extensive use of modeling tools to get the physical insights of how the cell operates. Although the scope is limited to solar cells, the knowledge learnt from this course would be relevant to other semiconductor/optoelectronic devices such as photodetectors, light emitting diodes, and transistors. The first few weeks of the course will provide a sound foundation of semiconductor device physics necessary for the later part of the course. The assignments will include problems involving analytical modeling and simulations using available software tools. There will be a final project of the course which could be either on fabricating/characterizing a low-cost solar cell prototype, or developing.

a numerical simulation, or an analytical/qualitative analysis of a relevant solar cell design problem.

This course is intended to provide a deep understanding about the fundamentals of optimal operation and control of power systems. The course

focuses on the understanding of power system operating states and characteristics of generating units. The solution methods of economic load

dispatch (ELD) and unit commitment (UC) are covered. The concepts and formulations of DC and AC optimal power flow (OPF) are described.

The control of generation including power and frequency control will be discussed. The concepts of steady-state voltage stability are explored. An

overview of main functions of SCADA system and energy management system (EMS) will be provided.

"This is an introductory-level Python-based course in data science to prepare students for scientific work, as well as advanced courses in data mining and machine learning. It is a hands-on course and involves weekly data analysis work.

We will start from descriptive statistics, develop an understanding of the pitfalls and biases in working with data, learn and practice exploratory data analysis (quality assessment and cleaning). The second half will focus on drawing inferences from data -- we will talk about setting up controlled experiments, hypothesis testing, and the foundational concepts of statistical and machine learning. We will also spend a major part of the course learning about data engineering i.e., tools and techniques for data collection, data storage and querying, and working with big data."

This course is only for students who have not done mathematics in A-levels, FSc, or the equivalent. The course covers the essential algebra and trigonometry required so that students can go on to due calculus afterwards. Topics include real and complex numbers, Cartesian and polar coordinates, functions, graphs of functions, log and exp functions, trigonometry, trigonometric functions, algebra, vectors and conic sections.

Partial Differential Equations (PDEs) permeate various scientific disciplines. This course deals with: Terminology; boundary and initial value problems; well- and ill-posed problems. the Laplace, wave and diffusion equations; the Klein-Gordon equation; Method of characteristics, separation of variables, integral transforms, Green's functions; potential scattering; dispersion and diffusion; regular and singular perturbation theory; asymptotes for complete solutions; Nonlinear PDEs: Converting nonlinear equations into linear PDEs; some exactly solvable cases; dimensional analysis and similarity; traveling waves; nonlinear diffusion and dispersion; the KdV, nonlinear Schrödinger and Sine-Gordon equations; reaction-diffusion equations; Fisher's equation; singular perturbations: boundary layers, homogenization. Variational Methods. Free-boundary value problems.

Polymers are at the heart of modern day science and technology innovations. For over a century, polymeric materials have been key contributors to the global socioeconomic development. Polymers are having revolutionizing impacts on a wide range of industries related to healthcare, renewable energy, electronics, textile, packaging, aerospace, automotive, and construction. The total global production of polymers was reported to be 322 million metric tons in the year 2015. Considering the importance of polymers, CHEM 515 is designed to be a comprehensive guide to the essential aspects of polymer science and technology. The contents of this course include introduction to different types of polymers, polymerization techniques, methods of controlling molecular architecture of polymers, synthesis of random and block copolymers, control of polymer reactivity and properties, structure-property relationships and techniques for polymer characterization. From application point of view, this course will highlight application of polymers as structural as well as functional elements in a wide range of endeavors addressing health, energy and environment related challenges. The course will also include understanding of molecular assembly of polymers at (molecular, nano, micro and macro levels), which is critical to their targeted application. Polymers are building blocks of life and have always been at the forefront of technological advancements. Understanding polymers is, therefore, essential to the training of science and engineering students.

This is an introductory-level Python-based course in data science to prepare students for scientific work, as well as advanced courses in data mining and machine learning. It is a hands-on course and involves weekly data analysis work.

We will start from descriptive statistics, develop an understanding of the pitfalls and biases in working with data, learn and practice exploratory data analysis (quality assessment and cleaning). The second half will focus on drawing inferences from data -- we will talk about setting up controlled experiments, hypothesis testing, and the foundational concepts of statistical and machine learning. We will also spend a major part of the course learning about data engineering i.e, tools and techniques for data collection, data storage and querying, and working with big data."

This is a first course in probability which provides preparation for further courses in stochastic processes, statistics, statistical mechanics and an understanding of the probability concepts essential for students who want to pursue studies in physical sciences, social sciences, economics, and engineering. The course starts with an introduction of probability terms and methods of computing simple and conditional probabilities. The concepts of discrete and random variables are covered. Special discrete and continuous probability distributions are explored with their real life applications.

### Q

This course will expose students to the core concepts in physical chemistry by building upon the fundamentals of undergrad and graduate courses. The course extends the understanding of these core concepts to the areas of quantum chemistry and spectroscopy.

This course builds on the narrative built in PHY 212 (Quantum Mechanics I) and is a natural sequel. The emphasis is twofold: (a) solving Schrodinger equation for central potential systems enabling exact solutions and (b) using basic approximation techniques in quantum mechanics. Throughout the course, we will explore pertinent examples.

### R

The course will cover core concepts of optics including geometrical optics, polarization, interference, diffraction, and Gaussian beams. Each covered concept will be augmented with discussions on industrial and research applications. The course will equip students with basic tools to take advance courses on optics and photonics.

### S

This core course overviews chemical thermodynamics with focus on the Zeroth, First, Second and Third laws of thermodynamics and how it relates to the equilibrium properties of macroscopic systems. Relations between the state functions that dictate the direction and extent of physical and/or chemical changes are discussed. Calculations involving work, heat, internal energy, heat capacities, enthalpy and entropy are discussed for various processes. Phase diagrams for single-component systems are discussed using Clausius-Clapeyron equation. The second part of the course introduces quantum mechanics and solution of Schrodinger equation for simple systems. It discusses wavefunctions, radial distribution functions, operators and eigenvalues, and how the position, momentum and energy of a particle are related with them in quantum mechanics. Periodic properties of elements are discussed in light of the electron-electron repulsion terms, radial distribution functions, the most probable radii, shielding and penetration, and the energies of orbitals.

This course will expose students to core concepts in physical chemistry building on the fundamentals covered in earlier courses. The course extends the understanding of these core concepts to the areas of chemical kinetics, electrochemical characterization, and statistical thermodynamics.

The following topics will be covered in the course:

• Web services and service-oriented architecture

• Semantic Web and ontologies

• Cloud computing and Internet of Things

• Business process composition and management

• Security and privacy

Generative AI stands at the cutting edge of today's artificial intelligence landscape, ushering in a new paradigm where machines not only understand intricate data patterns but also autonomously produce them. This in-depth course ventures into the fascinating world of Generative AI, cultivating a deep understanding of its potential to adeptly create, communicate, and innovate across diverse data forms. Students will gain hands-on experience with some of today's most renowned models, adapting them to unique use-cases while engaging with a vast array of topics—from foundational theories and principles to design, hands-on implementation, and thorough analysis of these systems. By the course's end, participants will be equipped to transition into the industry with tangible skills and a robust portfolio, contribute meaningfully to academic discourse by augmenting existing research or pioneering novel concepts, or embark on personal projects with an enhanced perspective and expertise.

This course introduces mathematical modeling techniques used in the study of signals and systems. Topics include sinusoids and periodic signals, spectrum of signals, sampling, frequency response, convolution and filtering, Fourier, Laplace and Z-transforms.

This course offers general introduction to software engineering: Practical problems of specifying, designing, and developing and testing software systems. It introduces students to the practical problems of specifying, designing, and developing and testing software systems by discussing concepts such as software processes and agile methods, and fundamental software development activities, from software specification through to system testing and maintenance. UML (Unified Modeling Language), the standard tool for expressing designs in software engineering, will be introduced.

This course will equip students with tools and techniques required to design reliable software systems. In this course, students are expected to develop ‘functional’ software system by following a software development lifecycle.

Key topics include:

- Introduction to software development life cycle models including classical and agile models.

- Introduction to the software requirements engineering process, including requirements elicitation, specification, and validation.

- Introduction to software design with the focus on architectural design including different software architecture models.

- Introduction to software testing and system reliability including testing methodologies and code inspections.

Some of the key software engineering activities like, software requirement management software configuration management, software quality assurance, and software estimation will be discussed in detail.

Some of the tools and their importance and use during the software development process will be discussed.

Capability Maturity Model Integration (CMMI) framework will be introduced to the students. Structure of CMMI will be discussed and detailed discussion of different process areas will be carried out.

### T

Transport Phenomena

It is a graduate-level course on computer networking research. It involves lectures, paper readings, discussions, and a semester-long research project. It will focus on the following 4 key areas in networking research:

• Datacenter Networking

• Cellular Networks

• Web, Video Streaming, and ICTD

• Internet Censorship & Privacy

For each of these areas, we will read classical research works as well as explore the state-of-the-art. Students will be required to write paper summaries and participate in class discussions. In addition, students will be expected to make presentations on assigned papers and participate in a semester-long research project.

This is an introductory course on computational theory. Various models of computations such as Finite State Machines, Context Free Grammars and Turing machines are studied in detail. All these models and their limitations are explored using Formal Languages. Although the main goal of this course is to prepare the students for advance concepts of computability and complexity theory, it also explores the practical implications of these computational models. For example, the course will apply these models in specific computer application domains. FSMs will be used to develop lexers, CFGs will be used to develop HTML grammars and parsers for interpretation by a web browser. Overall, the course will introduce the computational theory concepts with the intention to study their practical implications in state-of-the-art computer applications.

### V

The goal of this course is to provide a strong foundation for advanced microbiology course by familiarizing students with knowledge of bacteriology and virology. Microbiology is an exciting discipline with far-reaching impacts in human health and disease. This course will focus on the study of microbes in particular bacteria and viruses and their interrelationship with human disease. Understanding these relationships is essential in order to develop interventions to prevent infections in a community. The first quarter of the course will cover the basic principles of bacteriology including bacterial structure, growth, metabolism, genetics and general concepts of bacterial disease mechanisms. In the second quarter we will draw on the basic principles learned in the first quarter of the semester to understand bacteriology as it relates to human health and human disease. More precisely, the course will cover mechanism of disease and drug resistance and State-of-the-art technologies developed to understand pathogenesis. The next half of the course focus will be on viruses, another important pathogen that causes significant burden of disease every year. Globally viral infections kill approximately 2 million individuals every year. The higher burden of infections and fatalities caused by viruses are the result of their intrinsic diversity, which makes it difficult to treat and prevent viral infections. This part of the course will follow the same design as the part on bacteriology. However, in the next half the course will be focused on basic understanding of viral structures, assembly, replication, types of viruses, viral pathogenesis and finally vaccines.

This course provides the necessary background to design integrated circuits and systems for VLSI. These integrated circuits are required to provide very high performance while working under size, area and power constraints. The design of such electronic circuits is also complex owing to the high clock speeds, high logic density and problems in layout, simulation and fabrication. The course covers different design and architecture approaches for CMOS digital VLSI while also giving hands-on experience of design, verification and simulation of an integrated circuit using state-of-the-art CAD tools. The course will cover some of the advanced topics such as Memories, Mixed-Signal circuits etc.

### Fall 2023

### A

Course Code: CHEM 521

Course Instructor: Dr. Irshad Hussain, Dr. Ghayoor Abbas Chotana

This is an advanced course on Inorganic Chemistry and consists of two parts. First part deals with the molecular symmetry and its applications in explaining bonding in simple and complex molecules. The second part covers the chemistry of the coordination compounds.

Course Code: CS 310

Course Instructor: Dr. Basit Shafiq

Algorithms pervade a wide range of areas. Their effect is visible in our daily activities; whether searching something online, booking a trip, scheduling an event, finding directions, managing social media feeds etc. Applications of algorithms extend far beyond computer science. Businesses use them for process and product management, economists use them for predictions, biologists for determining similarity in genes, marketers for selling and advertising etc. This is a first undergraduate course on algorithms, where we‘ll look at a range of computing applications and follow a design process that includes (a) formulating the problem through precise notation, (b) understanding algorithm design techniques based on the structure of the problem, and (c) development of efficient solutions to solve these problems and prove their correctness. This course will discuss a number of design techniques such as greedy algorithms, divide and conquer, dynamic programming and network flow. The last module in the course will discuss computational intractability with focus on NP completeness

### B

Course Code: EE 558

Course Instructor: Dr. Ijaz Haider Naqvi

Batteries are ubiquitous in 21st century; from personal computers to residential storage units, from storage for renewable energy sources to high power electric vehicles, batteries are used as sources of energy and storage. They are used to power medical devices, home appliances and are used to store energy in grids. Li-ion batteries are gradually becoming the most commonly used type of battery. They are popular because of their low maintenance requirement, long lifetime, light weight, high energy density, and considerable depth of discharge, wide temperature range, low self-discharge rate, and fast charging capabilities.

### C

Course Code: BIO 313

Course Instructor: Dr. Amir Faisal

Cells are the most complicated entities known to humans and constitute every living organism in this world from bacteria to humans. Understanding the complex workings of different cells is at the heart of understanding how our bodies work. Cell biology, therefore, is one of the most fundamental subjects of biology. This course is organized into 4 modules that will help students understand how eukaryotic cells are organized and how they function. The first module will provide students with in depth understanding of the dynamic functions of cell membrane and various components of the cytoplast like endoplasmic reticulum, mitochondria and chloroplasts. The second module will cover intercellular interactions, cell signaling, and extra cellular environment. The third module will introduce students to cell division and differentiation. In this module students will learn about cytoskeleton, cell cycle regulation, cell death, cancer and stem cells. The course will conclude after discussing application of above mentioned principles in specialized immune cells that defend their host against invasion of pathogens.

Course Code: MATH 300

Course Instructor: Dr. Masood Hussain Shah

Course Code: BIO 531

Course Instructor: Dr. Safee Ullah Ch.

This course provides an introduction to computational biology introducing the tools and techniques important to study and analyze genomic data. This course emphasizes on the fundamentals of nucleic acid and protein sequence analysis, phylogenetic analysis, and the analysis of biological networks

Course Code: BIO 331

Course Instructor: Dr. Safee Ullah Ch.

The primary focus of the course is to understand theoretical foundation of some of the most widely used computational biology techniques. The principles and methods for pair-wise and multiple sequence analysis using hidden Markov models, phylogenetic analysis, protein sequence analysis and structure prediction are extensively covered. In addition systems biology is introduced at a glance with a significant amount of time spent on microarray analysis. The tutorials will provide hands-on training of programming in R and MATLAB with the aim of developing problem solving skills in computational biology research using scripting languages.

Course Code: CHEM 332

Course Instructor: Dr. Rahman Shah Zaib

This course is designed to apply the fundamental concepts learned during CHEM 231 to understand more about the important classes of organic compounds such as saturated/unsaturated hydrocarbons, alkyl halides, alcohols, aromatic and heterocyclic compounds, carboxylic acids and their derivatives. We will discuss the synthesis and reactions of these classes of organic compounds in more detail while explaining the orbital interactions and stereochemistry in particular. The applications of such compounds in life sciences and industry will also be discussed. On completion of this course, the students should be able to understand and propose mechanism of fairly complex organic reactions, especially those involving above mentioned classes of organic compounds.

Course Code: BIO 503

Course Instructor: Dr. Muhammad Shoaib, Dr. Khurram Bashir

Critical Thinking, Scientific Writing and Ethics is a three-credit hour course emphasizing on critical thinking and logics, discussions on Dos and Don'ts; of scientific writing as well as discussing scientific ethics. Students will be given assignments to enhance their understanding. Anyone interested in the course is welcome to join.

### D

Course Code: MATH 4013

Course Instructor: Dr. Waqas Ali Azhar

This course covers the fundamentals of Differential Geometry: Local and global geometry of curves and surfaces, Frenet frames, Total curvature, Minimal surfaces, Geodesics, Gaussian curvature, Differentiable manifolds, Tangent bundles and Riemannian manifolds.

Course Code: CS210

Course Instructor: Dr. Malik Jahan Khan

This course covers the mathematical foundations of computer science. The aim is to introduce the students to the fundamental techniques of discrete mathematics, which may be employed in a variety of mathematical disciplines, including fields in theoretical computer science, such as, algorithms, data structures, and complexity theory. An introduction to logic, proof techniques, sets, functions, and relations is made, along with an initiation to combinatorics, basic graph, and tree structures. A very brief introduction to number theory and discrete probability is made. Problems are formed mathematically and solved using available tools and techniques.

Course Code: EE 517

Course Instructor: Dr. Hassan Mohy-ud-Din

Deep Learning is a hierarchical learning methodology based on artificial neural networks which are algorithms inspired by the structure and function of the brain. It has applications in wide-range of industries these days such as face-recognisers working at massive scales, robotics, speech translation, text analysis, improving customer experience, autonomous vehicles etc.

In this course we will take a “hands-on approach” and start will the implementation of basic building blocks such as training a simple perceptron and move to design and train a deep convolution neural network. The course will concentrate in developing both mathematical knowledge and implementation capabilities. The implementations will be Python based using TensorFlow and Keras. After establishing our foundation in convolutional neural networks we will start looking into applications of deep learning in both spatial as well as time-series data and explore various network architectures suited for each. The objective is to help you build a career in AI and Machine learning, to make you comfortable enough that you can understand various learning problems and develop your own deep learning-based solutions.

### E

Course Code: PHY 204

Course Instructor: Dr. Rizwan Khalid

The course is a first introduction to Electricity and Magnetism. It will review static and dynamic electric and magnetic fields, as well as their inter-relationships. Physical models will be presented throughout the course, with a sprinkling of computational exercises and in-class demonstrations

Course Code: BIO 524

Course Instructor: Dr. Zaigham Shahzad

Evolutionary ideas link different fields of biology. This course provides an evolutionary context to understand biology. We will review the history of evolutionary thoughts, the forces of evolution, and the need for an extended evolutionary synthesis theory. We will also study the application of evolutionary studies to medicine and agriculture.

### F

Course Code: CHEM 231

Course Instructor: Dr. Irshad Hussain

This course is designed to introduce organic chemistry to Biology & Chemistry sophomore students by discussing the structure and reactivity of the major classes of organic compounds enabling the students to acquire the fundamental knowledge and skills to solve elementary problems in organic chemistry. On completion of this course, students should have the ability to analyze simple organic reactions, predict their mechanisms based on frontier orbitals interaction, and possible products including those that have not explicitly been discussed during the course.

Course Code: CHE 312

Course Instructor: Dr. Tauqeer Abbas

This is an introductory course that centers on fundamental chemical principles and processes that help understand and solve environmental challenges related to atmosphere, water and soil pollution. Students will also learn about the effects of anthropogenic activities on the chemistry of the Earth. Specific topics include air pollution (smog, particulate matter, greenhouse gases, ozone), water contaminants and purification, toxic organic chemicals and metals in the environment.

### G

Course Code: BIO 221

Course Instructor: Dr. Khurram Bashir

The intellectual framework of this course will introduce students to basic concepts in genetics and epigenetics. Both genetic and epigenetic inheritance patterns will be introduced with an emphasis how they influence our development. Different modules will cover classical genetics based on Mendelian laws and gene interactions which explain deviations from Mendel’s laws. In addition, microbial genetics will be explained to help understand how fundamentals of gene regulation were discovered. During this course, students will learn in great detail how forward and reverse genetics approaches in different model systems are employed to understand cellular function. Moreover, human genetics module will explain how genetics plays a major role by using alleles in humans to understand disease and development. Last but not the least, understanding quantitative genetics and population genetics will explain how mutagenic traits are investigated and how genes may evolve at a population level. How genetics has helped us understanding molecular and biochemical pathways of development is an important subject of this course.

### I

Course Code: EE 573

Course Instructor: Dr. Nadeem Ahmad Khan

Image and Video compression techniques can be regarded as the backbone of digital video communication and multimedia systems. After reviewing some basics of concepts of digital images and videos, this course is meant to familiarize students with the theory and standards of image and video compression and coding in today’s world and to enable them to appreciate and understand the ongoing research in this area. Assignments/ Home work & Project will be geared towards this goal. Basic background in Computer programming is expected for joining this class. Background in Signal and systems/ Digital Signal Processing is helpful Image and Video Coding.

Course Code: MATH 309

Course Instructor: Dr. Shaheen Nazir

Introduction to Analysis II is the sequel to Introduction to Analysis I, and together these two courses constitute the foundations of real analysis in mathematics. This course is designed to prepare students for future advanced analysis and functional analysis courses. It lays the foundation for several other areas, such as complex analysis, topology, dynamical systems, quantum mechanics, and mathematical statistics. The rigorous treatment of the subject in terms of theory and examples gives students the flavor of mathematical reasoning and intuition for other advanced topics in mathematics. Topics covered are Open, closed, and compact sets of real numbers. Sequences and series of functions, point wise and uniform convergence. Power series and Taylor series. Metric spaces: basic notions generalized from the setting of the real numbers.

Course Code: BIO 101

Course Instructor: Dr. Amir Faisal, Dr. Muhammad Tariq, and Dr. Safee Ullah Ch.

Introductory biology aims to provide a broad overview of biology as it stands today, exposing students to a variety of topics in modern molecular and cellular biology. The course is divided into four modules:**1. Macromolecules and Cell Biology**

We start with an introduction to the molecules of life and how they are organised into a cell, the basic unit of life in all living organisms. Students learn how cells communicate with each other, how they divide, and how they produce and consume energy. **2. Genes and Development**

The course then focuses on the organisation of genetic material and how various molecular, genetic and biochemical processes underlie the functioning of cells from replicating their genetic material for cell division to accurately producing essential proteins during development. **3. Omics and Systems Biology**

This module provides an overview of how modern biology is reliant on generation and analysis of big data and how this data can be utilised for a better understanding of biological systems.**4. Human Diseases and Drug Discovery**

In the end, we discuss how communicable and non-communicable human diseases are caused and how understanding the molecular mechanisms of these diseases allows us to develop more effective drugs. Manipulating genetic materials is at the heart of advances in life sciences that we see today from biomedical to agricultural sciences. This module also provides an overview of how the genetic makeup of organisms can be manipulated in the laboratory.

### M

Course Code: BIO 216

Course Instructor: Dr. Muhammad Shoaib, Dr. Muhammad Tariq

This course provides a comprehensive introduction to molecular biology and is designed for students interested in learning molecular mechanisms which control cellular processes in eukaryotes and prokaryotes. Topics include structure of nucleic acids and proteins, organization of genes, genomes, chromatin and chromosomes, DNA replication, repair, recombination, transcription, mRNA processing, protein synthesis and turnover, control of gene expression, signal transduction pathways, non-coding RNAs, evolution of biopolymers and origin of life.

Course Code: BIO 517

Course Instructor: Dr. Shaper Mirza

Microbial Pathogenesis refers to versatile mechanisms used by pathogens to evade our immune system and invade different niches in our body. The course will start with an overview of infection epidemiology followed by a discussion of niche-specific pathogenesis (respiratory, gastrointestinal, and genital tract pathogens) and will conclude with methods of infection prevention surveillance, and control. The course will be a combination of lectures and a review of current literature in the field of Molecular Pathogenesis.

Course Code: CHEM 221

Course Instructor: Dr. Ghayoor Abbas

This course covers simple bonding theories (VSEPR & VBT) used to describe bonding in main group compounds. Students will be introduced with the basics of coordination chemistry. The main focus of this course will be to provide a systematic presentation of the chemical applications of group theory with emphasis on the formal development of the subject and its applications to the physical methods of inorganic chemical compounds. Acid base chemistry and solid state chemistry.

Course Code: PHY 603

Course Instructor: Dr. Muhammad Faryad

This course introduces the basic principles of machine learning that includes the understanding of learning algorithms in supervised and unsupervised settings. The main focus of the course will be the study of predictive modeling techniques. Besides, we’ll pay special attention to topic modeling as well as inference and learning in graphical models.

### O

Course Code: MATH 341

Course Instructor: Dr. Kamran Rashid

Operations research has had an increasingly great impact on the management of organizations, including business, government, and military. Operations research involves the formulation of real-life situations into mathematical models, and then developing optimal solutions by application of various algorithms. The purpose of this course is to provide an appreciation of various techniques used in operations research, and their application in developing optimal solutions for real-life problems.

### P

Course Code: CHE 260

Course Instructor: Dr. Qandeel Almas

The course is primarily meant for SSE undergraduates who want to learn about fundamental principles of chemical engineering. Chemical engineering involves physics, chemistry, biology, and mathematics and their application in the production, transportation, and use of chemicals, materials and energy. By the end of the course, the students will be able to recognize the nomenclature of chemical engineering, use a systematic approach to solve chemical engineering problem, use effectively an accounting framework to solve material and energy balance problems and work effectively in teams.

### Q

Course Code: PHY 212

Course Instructor: Dr. Syed Moeez Hassan

This course introduces the basic framework of quantum mechanics with both introductory and advanced examples. It is designed to alleviate many of the weaknesses left over in traditional introductory quantum mechanics courses and revises and strengthens many concepts that usually create problems for students in other advanced courses that build on quantum mechanics. The course also introduces students to many advanced topics.

### R

Course Code: EE 562

Course Instructor: Dr. Muhammad Abubakr

Motion planning is the study of models and algorithms that reason about the movement of physical bodies such as humans, robots, and animals. This course focuses on motion planning for industrial manipulators and autonomous mobile robots such as unmanned aerial and ground vehicles. Topics include kinematic representations of movement, potential functions, sampling-based probabilistic planners, robot dynamics, multivariable control, and visual serving. Students will implement motion planning algorithms in simulation environments, read recent literature in the field, and complete a project that draws on the course material. The course bridges the theoretical gap between low-level regulatory control and higher-level AI in robots.

### S

Course Code: PHY 313

Course Instructor: Dr. Muhammad Faryad

Statistical mechanics is a Physics core course on essential thermodynamics and the understanding of systems with a large degree of freedom. The course begins with the studies of heat and thermodynamics. The topics studied include the laws of thermodynamics, the concepts of temperature, work, heat, and entropy. It will review basic concepts in probability theory, probability distributions and central limit theorem. Later on we will discuss concepts in statistical mechanics including macroscopic variables and thermodynamic equilibrium, fundamental assumptions of statistical mechanics, and micro-canonical, canonical and grand canonical ensembles. We will deal with the many body systems using Gibbs ensemble approach and will construct the microscopic picture of macroscopic thermodynamic quantities. The link between the microscopic interactions and macroscopic observables will be established. Furthermore, the equilibrium thermodynamics of ideal systems such as an ideal gas will be thoroughly studied. In summary, the course will formally develop classical and quantum statistical mechanics, and we will conclude with some interesting and revealing Physical applications.