I build fast, ship faster, and never stop learning.
Self-driven Software Engineering student based in Toronto operating at the intersection of full stack development and machine learning. I don't just study concepts, I apply them. I've competed in 10+ hackathons, shipping AI-powered platforms under 24–36 hour deadlines, and built personal projects like a full credit card fraud detection system independently from the ground up.
My stack spans React, Next.js, Node.js, FastAPI, Python, MongoDB, Firebase Auth on the web side, and scikit-learn, PyTorch, OpenCV, YOLOv8, Hugging Face Transformers, LLM integration (Cohere), NumPy on the ML side.
| 🏆 | 10+ hackathons competed — Mac-a-Thon 2026 (McMaster), KingHacks 2026 (Queen's) & more |
| 🤖 | Leveling up in PyTorch, LangChain & RAG pipelines, Cloud (AWS, GCP, Azure) & CI/CD |
| 🌐 | Full stack: React, Next.js, FastAPI, Python, MongoDB, Firebase + scikit-learn, PyTorch, OpenCV, YOLOv8, Hugging Face, LLM integration, NumPy |
| 📍 | Based in Toronto, ON |
Languages
Frameworks & Tools
| Project | Description | Tech |
|---|---|---|
| Mac-a-Park | Mac-a-Thon 2026 @ McMaster University — Real-time computer vision system using YOLOv8 & live video feeds to detect parking occupancy, with a FastAPI backend and Next.js dashboard | Python, OpenCV, YOLOv8, FastAPI, Next.js, React, MongoDB, TypeScript |
| ConnectKingston | KingHacks 2026 @ Queen's University — AI volunteer matching platform using Cohere LLM for intelligent ranking, with FastAPI backend & Firebase Auth | JS, React, Python, FastAPI, Cohere LLM, Firebase, MongoDB |
| CreditCardFraudDetector | Personal project — Random Forest fraud detection on 250K+ transactions. 92% Precision, 85% Recall, 88% F1-Score. Full stack with FastAPI & MongoDB | Python, scikit-learn, FastAPI, React, MongoDB, NumPy |
| Portfolio Website | Personal portfolio built from scratch with React | React, JS |
Always building. Always learning.