What I've built.
Two tracks, machine-learning systems and security tooling, plus a flagship that lives in both. Each links out to source, and several have live demos.
Things I built because they should exist.
tensorgrad
A tiny reverse-mode autodiff engine, full training pipeline in under 600 lines, with four optimizers, GPU support, and a pytest suite cross-checked against PyTorch.
toronto-bikeshare-ml
Demand-forecasting pipeline over ~19.2M trips and 878 stations, a PyTorch GRU forecaster served through a FastAPI + React app with an interactive map.
Rainy Days
NASA Space Apps 2025 (Toronto) 1st Runner-Up, predicting cloud-seeding potential from NASA MODIS satellite data with a multi-output regressor.
MRI Tumor CNN
A PyTorch convolutional neural network for binary classification of brain tumors from MRI scans, built as an applied deep-learning study after Google DevFest 2025.
Offensive work,
in the open.
Protocol fuzzing and hands-on security research, built and run in isolated lab environments.
Open to new
projects.
Internships, collaborations, or an interesting problem in security or machine learning. Feel free to reach out.