AI SWE Co-op @ Pitstop (Fullbay) | 3A CS @ University of Waterloo
I build highly optimized backend systems and AI-driven products, taking them from design to production. My core focus is on predictive analytics, document understanding, and building robust APIs that scale. I am currently interning as an AI Software Developer at Fullbay for my Spring 2026 co-op (May 2026 - August 2026).
- Languages: C/C++, Python, Java, Ruby, Bash, HTML, CSS, JavaScript, TypeScript, Racket
- AI/ML & Backend: React, PyTorch, FastAPI, REST Architectures
- Systems Engineering: Memory Management (RAII), Compiler Design, Custom Data Structures
Darwin Predictive Analytics Engine (Awarded Most Creative Data Visualization @ CxC 2026) Architected a REST API using FastAPI and PyTorch deep neural networks to simulate and visualize user interaction heatmaps for frontend web products.
WLP4 Compiler Engineered a C++ compiler for the WLP4 language (Waterloo Language Plus Pointers Plus Procedures). Implemented Simplified Maximal Munch scanning and SLR(1) parsing and utilized the Visitor Design Pattern to handle strict semantic analysis and code generation using RAII and OOP design concepts. Achived a 100% success rate across all test cases and architected a multi-pass optimization pipeline, reducing memory footprint by up to 8%.
University of Waterloo — Honours Computer Science
- GPA: 4.0/4.0
- Transferred from Honours Math to Computer Science after discovering my passion for programming & artificial intelligence
- Relevant Coursework: CS 241 Compiler Development, CS 246 Object-Oriented Software Engineering, CS 240 Data Structures, CS 245 Logic and Computation.
- CxC (Feb 2026): Winner — Most Creative Data Visualization
- DeltaHacks (Jan 2026)
- ChessHacks (Nov 2025)