Important
Data Scientist and ML Engineer specializing in bridging the gap between statistical inference and scalable AI engineering.
I focus on on-device ML, Graph Neural Networks, and LLM orchestration to solve real-world operational challenges.
- 🔬 Current Focus: Predictive modeling, RAG architectures, and local-first AI deployment.
- 🌱 Learning: Optimizing SLMs for edge devices and real-time vision.
- 💬 Ask me about: Using AI to automate inventory or building persistent memory for AI agents.
Prototypes built for speed, scale, and impact.
- 🥇 Video++ – A RAG-based education tool; 1st Place Winner at the AGI Ventures x Backboard Hackathon.
- 🛡️ AptosAI Guard – AI-driven security and anomaly detection for the Consensus Global Hackathon.
- ✂️ StanCut – AI-assisted media optimization tool.
Personal explorations in on-device AI and automation.
- 📦 VizCount – Real-time mobile inventory system using local-first OCR and lightweight vision models.
- 🤖 Tapasi – Experimental ML workflows and agentic automation.
Rigorous data science applied to business and social problems.
- 🎾 Tennis Central Capstone – Comprehensive analytics and operational strategy project.
- 📉 Customer Churn Prediction – Pipeline using SQL, Power BI, and ML to drive retention strategy.
- 💳 Credit Card Fraud Detection – Real-time transaction anomaly detection system.
- 📊 Canada Quality of Life Index – Multivariate analysis and storytelling using Power BI.
View Technical Proficiency & Credentials 🛠️
Languages & Tools:
Python SQL PyTorch TensorFlow Power BI Docker n8n
Certifications:
- NLP with Python for Machine Learning Essential Training – LinkedIn Learning
- Building Recommender Systems with Machine Learning and AI – LinkedIn Learning
- Master Microsoft BI – LinkedIn Learning
- Data Structures and Algorithm – LearnCodeOnline