I'm a Software Engineering student at McMaster (GPA: 3.93) graduating in April 2026. I'm passionate about building production-grade ML systems that actually ship — from optimizing transformer models on 128 A100 GPUs at Shopify to deploying computer vision systems for live sports broadcasting at Evertz.

Currently: Leading the software team (15 devs) at McMaster Exoskeleton, building a robotic lower limb exoskeleton with real-time control systems and gait prediction models.

Next: Returning to Shopify full-time as an ML Engineer in May 2026.

May 2025 – August 2025

• Optimized training pipeline for generative recommender transformer, cutting training time by 5% on 128 A100 GPU cluster (saved ~1.2 hours per run)
• Built and deployed uplift modeling system for personalized upgrade recommendations → $1M+ revenue impact with 2% conversion lift
• Implemented causal inference techniques and A/B testing frameworks to validate model performance across user segments
• Stack: PyTorch, Transformers, Causal Inference, A/B Testing, CUDA

May 2024 – April 2025

• Developed Faster R-CNN and YOLO object detection models achieving 75% improvement in real-time inference for broadcasting
• Integrated CV models with OpenCV for 2D-to-3D camera calibration, enabling real-time object tracking in live sports
• Leveraged Structure-From-Motion for 3D scene reconstruction — product demoed at IBC 2024 and NAB 2025
• Stack: PyTorch, YOLO, OpenCV, Structure-From-Motion

November 2024 – Present

• Leading 15 developers building a robotic lower limb exoskeleton with embedded control systems and safety mechanisms
• Designing gait prediction models using sensor fusion and time-series analysis to predict human movement patterns
• Implementing CI/CD pipelines and automated testing for robust embedded systems development
• Stack: Python, Embedded Systems, Time-Series Analysis, CI/CD

End-to-end encrypted messaging application with military-grade security

• Stack: Flask, React Native, Firebase, AES-256
• Features: Real-time async encryption/decryption for concurrent sessions
• Impact: Production-grade security architecture with zero-knowledge design

🧠 ML Research & Engineering

• Optimizing transformer training pipelines and building production recommender systems
• Developing gait prediction models using sensor fusion for the McMaster Exoskeleton
• Exploring causal inference techniques for personalized recommendations

⚙️ Infrastructure & Systems

• Building scalable MLOps pipelines for large-scale GPU clusters
• Designing real-time embedded control systems for robotics applications
• Deep diving into CUDA optimization and distributed training

When I'm not training models or writing code, you'll find me on the basketball court, at the gym, or gaming. I'm big into staying up to date with the latest tech and agentic workflows. Always looking to learn something new and build cool stuff.