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. The following courses will be offered in the Fall semester.
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
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.
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: 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.
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 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
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.
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.
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: 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.
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.
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: 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.
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.
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: 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.
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: 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.
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.
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.
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.
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.
