Research Interests

• Optimization & Decision-Making Under Uncertainty: Developing robust mathematical models to enhance energy efficiency and reduce operational costs.
• Machine Learning & Reinforcement Learning: Leveraging AI techniques for real-time decision-making in V2B and transit operations.
• EV Charging & Grid Interaction: Studying the interplay between EVs and the power grid to develop cost-effective and sustainable energy solutions.

Skills

• Programming: Python, C++, Java, JavaScript, SQL
• Frameworks & Tools: PyTorch, CPLEX, PySpark, Scikit-learn, D3.js
• Platforms: Linux, AWS, Docker, SQL
• Soft Skills: Leadership, Public Speaking, Technical Writing, Event Management

Projects

• Vehicle-to-Building (V2B) Optimization: Developing negotiation strategies to minimize energy costs and grid impact.
• Electric Bus Scheduling & Charging Optimization: Designing models to optimize fleet management while considering power grid constraints.
• Emergency Response Center Planning: Utilizing spatial-temporal data analysis to identify optimal locations for emergency response hubs.