Automatically Detecting Numerical Instability in Machine Learning Applications via Soft Assertions
FSE 2025 paper introducing Soft Assertions to detect and trigger numerical instability bugs in ML applications.
Anwar Zahid
I am a graduate student in computer science at Iowa State University. My work is centered on reliable AI systems, with an emphasis on testing, debugging, and understanding how large language models and machine learning systems behave in practice.
Selected projects from existing repository entries.
FSE 2025 paper introducing Soft Assertions to detect and trigger numerical instability bugs in ML applications.
Contributed to the LLNL Varity project by implementing HIP backend generation for GPU kernel testing, enabling cross-platform numerical consistency evaluation.
Extended a class project to evaluate hate speech detection models using geographical metadata. Later adapted for large language model testing and published in 2025.
Developed a real-time face recognition and spoof detection system for FinTech applications, enhancing security for remote banking verification.
Implemented Single Sign-On authentication for PRP system, enabling secure unified access across parliamentary resource modules.
Implemented and evaluated ML algorithms for natural language processing tasks. Later extended for LLM experiments and paper publication.
Developed an intelligent Othello game-playing agent using adversarial search algorithms and heuristic evaluation functions.
Created a Mancala game engine with an AI opponent using minimax and heuristic strategies.
Built a ray tracing engine from scratch to render 3D scenes with reflection, refraction, and shading.
Extended the Nachos instructional OS to implement thread scheduling, virtual memory, and file system operations.
Implemented and tested channel equalization algorithms to improve signal quality in noisy communication environments.
Selected writing and publications will be added here.
The easiest way to reach me is by email. You can also find my code and academic profiles through the links below.