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Optimization Consultant | Operations Research | Market Equilibrium Methods
Professor of Computer Science (Emeritus)
35+ Years of Algorithmic Innovation Optimization scientist and educator with extensive experience designing constrained optimization algorithms and translating theoretical advances into deployed, production-grade systems.
Pioneer in Quadratic Programming: Developed the first interior-point method for convex quadratic programming (ACM STOC 1986).
Policy Guidance: Developed machine-learning prescriptive models for national COVID-19 policy advice to NITI Aayog (Govt. of India).
Commercial & Academic Leadership: Inventor on 14 U.S. patents/applications, co-founded a vehicle-routing venture, and supervised 9 Ph.D. & 25+ M.S. researchers.
🧮 Mathematical & Network Opt.
🧮 Mathematical & Network Opt.
• Interior-point methods
• Convex quadratic programming
• Multi-commodity flows
• Vehicle routing & scheduling
⚖️ Equilibrium & Game Theory
⚖️ Equilibrium & Game Theory
• Market equilibrium pricing
• Cournot & two-sided markets
• Nash / Stackelberg equilibria
• Price of Anarchy analysis
📊 Analytics & Strategy
📊 Analytics & Strategy
• Policy-grade ML models
• Epidemic forecasting
• Learning-based search structures
• Spectrum resource allocation
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