Hi there! I’m Aziz Zayed, an MSc student at McGill University specializing in compilers and programming languages. My current research focuses on equality saturation-based compiler optimization. My most recent publication proposed a way to optimize MLIR using equality saturation on e-graphs: DialEgg: A Dialect-Agnostic MLIR Optimizer using Equality Saturation with Egglog, which I presented at CGO in March 2025.
With a diverse range of industry and research experiences, I’ve had the opportunity to work on impactful projects with world-class organizations:
- Morgan Stanley: I built machine learning models to detect fraud and anomalies in transactions, strengthening security for clients.
- NVIDIA: I designed and tested OmniGraph nodes for the Omniverse compute engine, improving ease-of-use and achieving a 20% increase in code coverage.
- Amazon: Hosted risk assessment ML models for detecting risky buys in the supply chain, reducing request latency by 35% and automating deployments.
- AWS: Enhanced GAN model support within Deep Java Library (DJL), introducing real-world examples to improve DJL’s usability for customers like Netflix.
Check out my resume for more details.
Outside of research and work, I love learning and building things (i.e. the engineering degree 🙂). Feel free to explore my projects, blog and publications to see what I’ve been working on. I also enjoy diving into topics on religion and philosophy, as well as spending time exploring the beauty of nature.