I'm Varun Jain, a researcher and graduate of McMaster University's Integrated Biomedical Engineering and Health Sciences (iBioMed) program, where I completed both my undergraduate and graduate degrees. My research spans orthopaedic surgery methodology, clinical evidence synthesis, and biomechanics, with a focus on improving how research findings are interpreted and reported in clinical settings.
On the research side, I work with systematic review methodology, statistical fragility analysis, and evidence appraisal. On the technical side, I am proficient in Python, MATLAB, JavaScript, and Swift, with hands-on experience building IoT and biomedical devices using Arduino and Raspberry Pi. I also have experience with PCB design (KiCAD) and CAD (SolidWorks).
I'm drawn to biomedical engineering, biotechnology, and biomechanics, particularly how engineering principles and rigorous research methodology can be applied together to advance healthcare. I enjoy building things as much as studying them.
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Personal Project · 2026
An automatically updated database tracking player injuries across the Top 5 UEFA leagues, MLB, and NFL. Continuously analyzes injury reports to determine trends in injury type, severity, and return-to-play (RTP) outcomes, providing a structured foundation for cross-sport injury epidemiology.
Personal Project · 2026
A multi-agent AI system designed to optimize clinical workflows in musculoskeletal (MSK) care. Agents operate across tasks spanning patient intake, care pathway selection, and post-surgical follow-up, with behavior grounded in current scientific literature.
Personal Project · 2026
A live sports score display hosted on a Raspberry Pi and connected to an LED screen. Retrieves real-time score data for user-selected teams and leagues, cycling through each active game in a rotating display. Built for continuous ambient use on game days.
Personal Project · 2025
A Flask web dashboard that pulls personal workout data from the Hevy API, generates training volume and frequency charts, and auto-refreshes every 30 minutes. Deployed on Render.
Hack the North 2019 · Deloitte Perfect Pitch Award
A React Native app that detects improper form during compound fitness lifts in real time using computer vision. A machine learning model processes skeletal video data and returns feedback through a Node.js REST API.
McMaster University · March 2019
An Android application that monitors real-time sensor data from a Raspberry Pi over MQTT to assess a user's risk of coronary artery disease symptoms. Integrated the Twilio API to send automated alerts when risk indicators are detected.
Hack Western V · November 2018
A Google Chrome extension that calculates trip fuel costs directly within Google Maps based on the user's vehicle. Pulls real fuel economy data from the US Government database to provide accurate cost estimates across all vehicle models.
Hackathon · 2019 · Devpost People's Choice Award
An iOS app that uses CoreLocation and MapKit to create a geofence around a user's destination and sends a push notification when they enter the waking radius — solving the problem of commuters missing their stop.
ConversationHEALTH · 2018
A mental health chatbot built in collaboration with ConversationHEALTH, a startup, designed to inform users about mental health topics in a casual and interactive conversational format.
