About me

I am a Ph.D. student in Operations Research at the H. Milton Stewart School of Industrial and Systems Engineering (ISyE), Georgia Institute of Technology. Before joining Georgia Tech, I received my B.S. in Applied Mathematics (Honors, Concentration in Statistics) and B.A. in Computer Science from Bucknell University, graduating Summa Cum Laude.

My research sits at the intersection of optimization and machine learning, with a focus on:

  • Combinatorial optimization and integer programming — exact methods, decomposition, heuristics, and metaheuristics for hard discrete problems
  • Machine learning for operations research — optimization proxies for decomposition methods, and learning-based contextual stochastic optimization for real-time, large-scale decision making
  • Online learning and bandits — Pareto-regret bounds for stochastic and adversarial multi-objective bandits
  • Covering arrays and combinatorial interaction testing — structure of optimal solutions under constraints
  • Matrix analysis — numerical ranges and Crouzeix’s conjecture

My recent work includes the Proxy Benders Decomposition, which replaces Benders subproblem optimization with certified optimization proxies; end-to-end supply chain planning in the paper industry via column generation and Benders decomposition; Pareto-regret bounds for stochastic and adversarial multi-objective bandits; learning optimization proxies for real-time order fulfillment; and OPTAgent, which uses LLM agents to synthesize solver-selection policies (NeurIPS 2026 ML×OR Workshop). See my publications and research projects for details.

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