Connor Pink
I'm Connor Pink, currently completing an M.Sc. in Computer Science at the University of Guelph. My work spans medical imaging, generative AI, applied machine learning, internal tools, and front-end systems shaped to make technical work clearer and more usable.
Medical imaging, evaluation systems, and experiments that can be communicated clearly.
Recent work has focused on segmentation, generative modeling, and the tooling needed to compare methods rigorously without losing sight of usability or communication.
Some of my favourite projects, experiments, and technical work that I've done.
Deployed, in-progress, and open-source work across research and software development. Click on each for more information.
A full-stack movie watchlist application with account-based persistence, TMDB integration, editable saved entries, and containerized backend deployment.
A Raycast extension for searching media through Overseerr, checking availability, and sending requests into a Radarr / Sonarr workflow.
Here are some of my research projects, experiments, and writeups.
Research from my time at University of Guelph. Click on each for more information.
Research on synthetic tuberculosis chest X-ray generation using diffusion and GAN models, with downstream classifier experiments, realism metrics, and privacy-oriented evaluation.
A chest X-ray research pipeline combining tuberculosis classification, lung segmentation, and diffusion generation, with a current focus on segmentation model comparison and efficiency tradeoffs.
An applied research project for Nevvon that modeled application freezes through session analysis, stuckness heuristics, and predictive factor discovery.