I'm a Master's student in Operations Research at Columbia University with interests in optimization, machine learning, and data-driven decision making.
My work sits at the intersection of analytics, optimization, and AI, with applications in public policy, sustainability, healthcare, and operations.
- Optimization (MILP, Constraint Programming, Gurobi, OR-Tools)
- Machine Learning & Predictive Analytics
- Reinforcement Learning
- Deep Learning
- Dynamic Pricing & Decision Making Under Uncertainty
- Agentic AI and Retrieval-Augmented Generation (RAG)
- Childcare Desert Elimination – Facility location optimization for improving childcare accessibility
- NBA Scheduling Optimization – Constraint Programming approach for sports scheduling
- Healthcare Risk Classification – Machine learning models for patient outcome prediction
- EV Fleet Charging – Deep Q-Network (DQN) for online electric vehicle charging decisions
- Dynamic Pricing with Thompson Sampling – Bayesian learning for revenue optimization
- SolarIQ NYC – Geospatial and financial analytics platform for rooftop solar investment screening
- Agentic AI Workflows – Tool-augmented LLM systems with memory and RAG capabilities
- Optimization + Machine Learning Integration
- Decision-Focused Learning
- Sustainable Energy Systems
- Reinforcement Learning for Operations
- AI for Decision Support
Feel free to connect if you're interested in optimization, analytics, AI, or operations research.