Shlok Panchal

I build machine learning systems for medicine.

I’m a final-year Biomedical Engineering and Health Sciences student at McMaster, interested in clinical machine learning and cardiovascular health. Across this work, I value intellectual independence: reasoning from first principles instead of deferring to consensus, shipping ideas early to get feedback, and updating my priors as soon as the evidence points elsewhere.

Research

Stanford University

Applying supervised learning and statistical modeling to clinical time-series data.

Toronto General Hospital

Developing ML and foundation models for transplant outcomes using multicentre data.

Harvard Medical School

Developing LLM assistants using RLHF for interactive public health simulations.

Temerty Centre for AI Research

Training voice agents for multi-agent patient simulation and automated clinical assessment.

McMaster University

Studying pediatric blood-pressure patterns with regression and predictive modeling.

Elsewhere

I co-host AI-Med Amplified, a podcast with leading clinicians and researchers, and co-direct MedSprint, Canada’s largest biomedical hackathon. I also help run the OpenAI Student Collective at McMaster. Away from work, I’m usually running marathons, playing everything from classical to Bollywood on the piano, creating short films, or heading out for a hike— currently training for Kilimanjaro. Reach out! I’d love to hear what you’re building, swap ideas, or grab a coffee.