Featured projects spanning artificial intelligence, reinforcement learning research, continuous rate simulations, autonomous systems, and full-stack web applications.
Machine Learning & RL
Featured
Modular RL (Functional Core for PyTorch)
High-performance researcher-centric Reinforcement Learning library for PyTorch built on the Functional Core, Imperative Shell design pattern (JAX/RLax style architecture).
Computational neuroscience and spatial navigation model combining Continuous Attractor Networks (CAN) and hippocampal grid cell scaffolds for spatial localization in AnimalAI environments.
A modular PyTorch suite building incrementally from vanilla Deep Q-Networks (DQN) to full Rainbow DQN (Double DQN, Dueling, PER, Noisy Nets, n-Step, C51) and NFSP.
Production-ready embeddable React agent widget that interacts with users to generate occasion-aware outfits with head-to-toe visualization, item swapping, and editorial descriptions.
Full-stack appointment and room reservation application built for McGill School of Computer Science (COMP 307 Competition Project) with MariaDB, Express, React 19, JWT auth, and .ics calendar exports.
Database-driven productivity system leveraging AI to bridge unstructured human thoughts into structured, prioritized execution plans with triage queues and review workflows.
Empirical evaluation of Deep Counterfactual Regret Minimization (DeepCFR) and Neural Fictitious Self-Play (NFSP) evaluated against Rainbow DQN in Google OpenSpiel imperfect-information games.