AI Engineer · ML Researcher · Systems Builder

I’m a computer scientist focused on robust, secure, and efficient AI for high-stakes environments - where ML systems interact with complex software stacks, human operators, or physical hardware.

My work spans:

• Small language models & efficient training/inference
• Autonomous agents for security and system analysis
• RL for robotic locomotion and competitive environments
• End-to-end ML systems: from data collection to deployment and monitoring

Technical Stack

Languages Python · C++ · C · Java · Bash

ML / AI PyTorch · PyTorch Lightning · TensorFlow · Keras · JAX · scikit-learn · NumPy · Pandas · Hugging Face · LangChain · Jupyter · OpenCV · OpenGL

Data & Cloud PostgreSQL · Databricks · Firebase · Google Cloud · AWS · Azure

Systems & Tooling Linux · Docker · Conda · VMware · CUDA · ROS

Experience

• AI Researcher – Vector Institute (R3 Lab, Colin Raffel) Research on small language model ensembles and model distillation, focusing on training, coordination, and efficient inference.

• AI Lifecycle, Resource Use & Efficiency – Obvia Worked on AI lifecycle, resrouce analysis and efficiency research, from experimentation to deployment and monitoring.

• ML Engineer – McGill AI Lab Built an sEMG stack and ML pipeline for real-time neuromuscular decoding, designing robust transformer-based models for multi-channel time-series signals.

• C++ Engine and AI Tool Development – Activision Blizzard C++ game engine development and optimization; internal AI tooling for programming workflows and developer productivity.

• Technical AI/AGI Advisor – United Nations Council of Presidents Advised heads of state on AI/AGI impacts, cybersecurity, and frontier-model safety; contributed to global governance frameworks for the 80th UN General Assembly.

• Security & CTF – UofTCTF Play capture-the-flag competitions with team focusing on software security, exploitation, specializing in AI redteaming.