Muhammad Ali Gulzar

Muhammad Ali Gulzar is an Assistant Professor in the Department of Computer Science at Virginia Tech and an Amazon Scholar at Amazon Web Services. He holds a Ph.D. (2020) and B.S. (2014) in Computer Science from UCLA and Lahore University of Management Sciences, respectively. His research focuses on improving developer productivity through automated debugging and testing for emerging software domains, including data-intensive systems, machine learning applications, and computational notebooks.

Education

• Ph.D., Computer Science, University of California, Los Angeles (2020)
• B.S., Computer Science, Lahore University of Management Sciences, Pakistan (2014)

Research Interests

Dr. Gulzar redesigns software productivity tools for emerging applications across three areas: (1) automated tracking-code localization in web applications, (2) re-engineering testing/debugging for data-intensive systems (e.g., Apache Spark), and (3) advancing testing/debugging in federated learning. His work includes projects like TraceFL for federated learning interpretability, NoT.JS for JavaScript tracking blocking, and MeanCache for LLM caching.

Recent Contributions

Recent papers address accessibility issues in ad-driven web pages (ICSE 2025), interpretability in federated learning (ICSE 2025), and notebook executability (MSR 2025). His team received the ACM CCS 2024 Distinguished Artifact Award for tracking JavaScript function analysis and a 2024-25 Amazon-VT Award for semantic caching research.

Grants & Projects

• CCI-funded project on web ad transparency/accessibility engineering
• Amazon Scholar collaboration on productivity tools

Student Contributions

Recent advisees include Abdul Haddi Amjad (ad accessibility), Waris Gill (Federated Learning), and Tien Nguyen (notebook analysis). Students have contributed to industry-relevant tools like GitMeter for evidence-based hiring and DeSQL for SQL debugging.