Bilal Siddiqui, PhD
Assistant Professor of Instruction, Statistics and Data Science
Contact
- SPI 420B - San Pedro I, 506 Dolorosa St.
- bilal.siddiqui@utsa.edu
Bio
I began my journey at The University of Texas at San Antonio in 2013 as an undecided undergraduate with engineering aspirations. During my sophomore year, I settled on Computer Science as a base to launch my career due to its versatility and have never looked back. By 2017, I had completed my BS in Computer Science and decided to pursue graduate studies. My doctoral studies began in June 2018 with a Presidential Distinguished Research Fellowship (PDRF) award from the Graduate School. After nearly six years of research, I concluded my PhD in April 2024 with a dissertation that presented novel techniques for parameter reduction in neural networks.
As part of my current appointment, I oversee the Graduate Certificate in Data Science within University College, where I also teach their Machine Learning and Data Science courses. When it comes to teaching, I like to promote active learning, and I seek to encourage learning through mistakes by providing multiple extra-credit activities per week (such as five-minute lecture quizzes) to reinforce the material. In my opinion, questions are the silver bullet to learning; they are how we explore and communicate in this simulation. It should be of no surprise that I employ the Socratic method, and I find that it helps anchor students to their class materials. I like to encourage discussions on problems because it often allows me to nudge the class towards better reasoning for their answers. In my view, teaching and research are two sides of the same coin, where teaching solidifies the known into understanding and research is an exploration building oZ the former. Therefore, I think it’s better to slowly learn with understanding than to blitz through potentially more material without internalizing how to use and apply the knowledge.
I often think about intelligence, particularly its imitations in the form of Machine Learning and how these imitations can be distilled into their simplest forms (parameter eZicient neural nets - my research). When not researching, teaching, or learning, I like to investigate the hows and whys of things, which may explain my hobbies of game development and film analysis. I grew up watching and reading science fiction and found any material that had “Star” in its title thrilling. These days, I gravitate more towards puzzle games like bitburner, shenzen i/o, and occasionally TV shows - two I recently enjoyed, The Sandman and Three-Body.
Degrees
- PhD, The University of Texas at San Antonio
