Rishi Shah – Machine Learning Research Engineer

ABOUT ME

Schulich Leader Scholar at McMaster University, one of Canada's top 50 entrepreneurial engineers that was awarded $120,000.
Engineered a biologically inspired recurrent vision model that outperformed MIT’s CORNet-S in adversarial robustness across MNIST, CIFAR, and ImageNet100.
Worked with Synaptive Medical and real surgeons to develop a surgical-vision system trained on live operating-room data, achieving 95% tool segmentation accuracy for real-time surgical guidance.
Founded Hack49 Global, a worldwide hackathon with 950+ participants from 40+ countries, securing $19,000+ in sponsorships
Built Sentinel, a hardware-aware static analysis system with a custom language server, performing RAM and Flash estimation, pin-mapping, and 50+ embedded validations before compilation.

PROJECTS

From Pixels to Precision

Partnered with Synaptive Medical and Robarts Research Institute to build surgical-vision AI system achieving 95% tool-segmentation accuracy for real-time guidance. Bronze Medal at Canada-Wide Science Fair for fluorescence-guided surgery support with <0.12s per image processing.

Adversarial Robustness Research

Engineered a bio-inspired recurrent vision model achieving 97.82% adversarial robustness, outperforming MIT's CORNet-S across MNIST, CIFAR, and ImageNet100. Integrated learnable prefiltering, gated recurrence, and denoise-scaling without requiring any adversarial training.

Sentinel

First hardware-aware static analyzer for embedded systems performing RAM/Flash estimation, pin-mapping, and 50+ validations before compilation. Built a custom Language Server Protocol integration with VS Code for real-time hardware-intelligent error detection.

Adaptive Learning Robot

Built a dual-system robot using Cohere LLMs and real-time search that learns new skills instantly from natural language without pre-training. Placed Top 32 out of 256 projects at Hack the North with 2 custom 3-DOF robotic arms executing smooth motions from messy instructions.

Zephyr AI Assistant

Keyboard-activated AI assistant with dual interface combining instant popup access and powerful dashboard for seamless workflow integration. Leverages Groq's Llama 3.1 8B for voice commands, intelligent memory, and controls Spotify, weather, news, calendar, and project tracking.

DermAI Medical Assistant

Medical AI platform combining DenseNet121 classification trained on 19,000+ DermNet images with RAG-powered chatbot for comprehensive triage. Provides instant dermatological assessment and personalized health guidance through dual AI architecture.

Pose Estimation Model

Real-time human pose detection system using Keypoint R-CNN ResNet-50 FPN for security and surveillance applications. Tracks 17 skeletal keypoints with OpenCV integration for automated behavior analysis in footage.

Gesture Controlled Robotic Arm

Computer vision-controlled robotic arm responding to hand gestures in real-time using MediaPipe and Arduino. Demonstrates natural human-robot interaction with 6-DOF movement mapped from gesture recognition.