Internship

Applied Science Intern, Amazon (Summer 2025)

• Formulated a stochastic programming model to allocate package volumes across delivery channels under demand uncertainty.

• Built a large-scale MILP framework with integrated neural network surrogates to capture complex routing and labor planning dynamics.

Research Science Intern (contract), Microsoft (Summer 2025)

• Designed graph-based code understanding methods that surpass traditional embedding retrieval, enhancing AI coding agents’ global codebase comprehension.

• Achieved agent-level performance in an agentless framework using graph representations, cutting cost and latency by over 95% compared to agent-based SOTA method.

Fulltime

Senior Consultant, Energy & Environmental Economics (2018 - 2021)

• Developed Python-based power grid capacity planning optimization model to support the state of California, New York, and 10+ large utilities in policy design and resource planning.

• Developed a market price forecasting product, integrating assumption data preprocessing, commercial optimization and simulation software (Aurora, PLEXOS), and large-scale data visualization (SQL, Python). Enabled data-driven investment decisions for 30+ investors, influencing $1B+ in utility-scale energy projects.

• Managed private and public sector clients and a six-person modeling team.

Associate, ICF Consulting (2016 - 2018)

• Designed and implemented Tanzania's first SQL database and capacity expansion model for power grid management and planning.

• Led power flow modeling for power grid transmission analysis for multiple U.S. regional transmission organizations.