Dr. Ali R. Butt is a Professor of Computer Science (and ECE by courtesy) and Associate Department Head for Faculty Development in CS@Virginia Tech. He is an ACM Distinguished Member. He received his Ph.D. degree in Electrical and Computer Engineering from Purdue University in 2006, and B.Sc. in Electrical Engineering from UET Lahore in 2000. He is a recipient of a number of awards such as the NSF CAREER Award and IBM Faculty Awards. He has served as the Associate Editor for IEEE Transactions on Cloud Computing, ACM Transactions on Storage, and IEEE Transactions on Parallel and Distributed Systems,  He is an alumni of the National Academy of Engineering's US Frontiers of Engineering (FOE) Symposium and National Academy of Science's AA Symposium on Sensor Science. Ali's research interests are in: cloud and high-performance computing systems; systems support for machine and deep learning applications; file, I/O, and storage systems; distributed systems; and large-scale experimental computer systems. At Virginia Tech he leads the Distributed Systems & Storage Laboratory (DSSL).

The performance of object instance segmentation in remote sensing images has been greatly improved through the introduction of many landmark frameworks based on convolutional neural network. However, segmentation of closely built properties with variable sizes and no definite pattern, a common trait in developing countries, is still a challenging task. Accurate segmentation information of residential and commercial properties built or non-built in a given region is of high value for many applications e.g. estimation of disaster damage and restoration, calculation of property tax, analysis of urban growth and population density in less-developed countries. In this research, we present a novel framework to extract residential blocks as well as accurate plot instances within those blocks in residential societies, where building density is high. We employ the state-of-the-art instance segmentation algorithm, Mask R-CNN as a backbone framework and further improve the segmentation results by adding a grid estimation approach that utilizes different aspects of statistical information from the Mask-RCNN predictions to overcome the issues of high variability in structure and building patterns. We also provide a large annotated dataset containing over 800 images of densely built societies in different cities in Pakistan.

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Evaluation Committee:

Dr. Murtaza Taj (Supervisor)

Dr. Fareed Zafar (Evaluator)

Directed graphs abstracting biological entities and their interactions capture the systematic biomolecular function and allow systems biologists to simulate systems-level behavior. However, the construction of such graphs or networks is cumbersome and requires expert literature review. Automated natural language processing approaches can be employed to overcome this hurdle. The currently available techniques are limited in discovering novel interactions from literature as well as in building reliable models. We propose to combine state-of-the-art machine reading techniques with biological interactions present in online molecular databases. The outcomes from this approach can help provide literature-supported and biologically viable interactions for onward inclusion into network models. In addition, we propose to use meta-heuristic techniques to optimize these networks so that simulation results match experimental data or known biological behavior. The resulting pipeline can produce simulation-ready and biologically plausible network models in a semi-automated manner.

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Committee: Dr. Safee Ullah Chaudhary (Supervisor), Dr. Basit Shafiq (Examiner)

Dr. Hashim is a postdoctoral researcher in computer science at the University of Illinois at Urbana-Champaign, working with Vikram Adve and Sasa Misailovic. In April 2021, he completed his PhD from the CS department at the University of Illinois at Urbana-Champaign, advised by Vikram Adve. Hashim works on compilers, systems for machine learning, and program analysis. His PhD thesis focuses on compiler and runtime systems for end-to-end accuracy-aware optimization of tensor-based programs running on heterogeneous edge compute hardware. Hashim’s earlier PhD work includes code size reduction techniques via software specialization. In his research, he has closely collaborated with Industry and Labs, including IBM Research, SRI International, Earthsense, Amazon, and Argonne National Lab. Teams at IBM Research use the ApproxHPVM compiler infrastructure for compiling programs for a custom heterogeneous SoC. Earthsense (a startup for agriculture robots) uses ApproxCaliper, an application-aware neural network optimization framework for improving the system performance for their resource-constrained agriculture robots. Hashim is a recipient of the Sohaib and Sara Abbasi Fellowship at the University of Illinois.

Zoom Meeting Link: here. 

Meeting ID:  984 9963 3901

Passcode:  576520

Workshop Agenda:

Please refer to the workshop datasheet here. 

Prerequisites:

The prerequisites for this workshop include understanding fundamental programming concepts in Python 3, such as functions, loops, dictionaries, and arrays; familiarity with Pandas data structures; and understanding how to compute a regression line.

Suggested materials to satisfy prerequisites: Python Beginner’s Guide.

Questions?

Contact the instructor (Dr. Abdul Bais, abdul.bais@lums.edu.pk)

Fawad Ahmad is a Ph.D. candidate in the Computer Science Department at the University of Southern California. He received his undergraduate degree in Electrical Engineering from the University of Engineering and Technology, Peshawar (UETP) where he was the recipient of the Presidential Gold Medal. His research interests are in networks/systems, more specifically in mobile systems. During his Ph.D. he has interned at Microsoft Research and NEC Laboratories. He received the best paper runner-up award at MobiSys 2018. His work on autonomous vehicles was adopted by General Motors with two global patents. He was also the finalist for the Qualcomm Innovation Fellowship in 2019.

Mr. Qasim M. Assad will be talking about “Mobile Gaming Industry and What It Has to Offer” on Friday, December 10, 2021, at 7:00pm PKST via Zoom. This seminar is organized by the Department of Computer Science at SBASSE, LUMS.

About the speaker:

Mr. Qasim graduated from FAST with bachelors in telecom engineering. He started his career as a game developer and worked in top studios in the country. Currently he is heading Mindstorm Studios Pakistan office as Studio Director. While leading the teams at studio his responsibility is to ensure speedy ideation, high quality of games and keeping the studio up to date with global trends. 

Speaker’s biography:

Qasim graduated from FAST with bachelors in telecom engineering. He started his career as a game developer and worked in top studios in the country. Currently he is heading Mindstorm Studios Pakistan office as Studio Director. While leading the teams at studio his responsibility is to ensure speedy ideation,  high quality of games and keeping the studio up to date with global trends. 

Join the talk:

https://lums-edu-pk.zoom.us/j/91826132749?pwd=WkliNjdVSVRMazBFaUU1NzMycDk0UT09 
Meeting ID: 918 2613 2749
Passcode: 831049
 

Ms. Sadaf Rehman will be talking about “Changing the World by Teaching Coding” on Thursday, December 2, 2021 at 2pm PKST.

Venue for in-person attendees: SBASSE 10-202

Online attendees can join via Zoom link: https://us02web.zoom.us/j/84696584740?pwd=UGxqQ3YzL2xVdjc5czV6Z3BGNmlCUT09 

Purpose of the Seminar: 

We would like to speak about our experience with teaching children coding, the bottlenecks we have faced with scaling, and how we have to re-think traditional teaching models in schools, and how college students in STEM fields today can help in building a better future not just for Pakistan but for other low-resource countries that are grappling with a tech-centric future.

About the speaker:

Sadaf has nearly two decades of experience in Pakistan's nonprofit education and skills training space, driving positive social change for youth. She has previously served as Pakistan Country Director for Generation Youth Employment, a McKinsey-founded skills training nonprofit. She also served as technical advisor to the Punjab Skills Development Fund, a $200m semi-government fund created by the Government of Punjab and DFID. Her previous experience includes The Citizens Foundation, the world’s largest chain of nonprofit schools, and Acumen Pakistan, an affiliate of Acumen, a US-based impact investment fund. She has consulted for LUMS, a leading not-for-profit university, CIRCLE Women, a grassroots digital & financial literacy nonprofit, RAVI Foundation's Infinity School of Engineers, and Pakistan Children’s Heart Foundation (PCHF), among others. She is also the co-founder of Codeschool. pk, an ed-tech STEM program, is reaching students in 10 countries. She trained as an IB instructor in 2017, has an undergraduate degree in computer science and math, and an MBA from LUMS, where she received a gold medal for first place overall.

Please find below some useful links:

• Codeschool.pk logo
• Link to Codeschool.pk related photographs and videos

Dr. Sadaf Alam will be talking about “Zero Trust Security Model Implementation Challenges for High-Performance Computing” on Friday, December 10, 2021 at 5pm PKST. 

To join please use this Zoom meeting link: https://lums-edu-pk.zoom.us/j/92523801204?pwd=dlpPSUZyRWRKZXNubWhhS01ld0VqUT09 

About the speaker:

Sadaf Alam is Chief Technology Officer (CTO) at the Swiss National Supercomputing Centre (CSCS) in Lugano, Switzerland. Dr. Alam studied computer science at the University of Edinburgh, UK, where she received her Ph.D. in 2004. Until March 2009, she was a computer scientist at the Oak Ridge National Laboratory, USA. In her role as the CTO, she ensures end-to-end integrity of HPC systems and storage solutions and leads strategic projects at the centre. She has held different roles at CSCS including group lead of future systems, chief architect, and head of operations. She is a member of ACM, ACM-W, SIGHPC and Women in HPC. 

Dr. Farhan Riaz will be talking about “Biomedical Signal and Image Processing: Challenges and Future Directions” on Friday, November 19, 2021, at 10:30 AM. This is a CS Research Seminar.

Venue for in-person attendees: SSE 10-301

Please join us via Zoom meeting link: https://lums-edu-pk.zoom.us/j/8353602730?pwd=emFaM21hNGtWNHhHZ0dmZm5ueFZqUT09

About the speaker:

Dr. Farhan Riaz received his BE degree from National University of Sciences and Technology, Islamabad, Pakistan in 2004, MS degree from Technical University of Munich, Germany in 2007 and PhD degree from University of Porto, Portugal in 2012. Since 2012, he is serving as an Associate Professor at the National University of Sciences and Technology, Islamabad, Pakistan. He has about 10 years of experience in biomedical signal and image processing, applied machine learning and computer vision. The applied areas of his research include dermoscopic image analysis, analysis of gastroenterology images, processing of PPG signals, processing of EEG signals, processing of PCG signals and processing of heart ultrasound videos. He is working in close collaboration with Instituto de Telecomunicacoes, Porto, Portugal for pursuing his research interests where he regularly visits as a consultant on computer vision on various projects. He has 60+ publications in impact factor international journals and peer reviewed conference publications.