Los Angeles, California, United States
AI | Optimization | ML | Social Good | Computational Sustainability ---- I work on developing scalable solution techniques for solving large-scale real-world optimization problems, merging ideas from algorithm design, operations research and machine learning. I am keen on bringing these state-of-the-art methodologies to problem domains that have important societal impact. In particular, I work on predictive and optimization problems related to habitat wildlife conservation and curbing illegal wildlife poaching and trafficking, as well as urban infrastructure resilience to disasters and climate change, among others.
College of Computing School of Computation Sciences and Engineering
Achieving sustainability requires balancing social, environmental and economic needs in the face of scarce resources and hence optimization and decision problems lie in the heart of many sustainability issues. I develop models and solution techniques for large-scale real-world optimization problems that arise in sustainability, with a strong emphasis on conservation planning.
Studied hidden structure in combinatorial decision and optimization problems that can explain the surprisingly good scaling behavior of search algorithms on real-world problems (e.g. from verification and product configuration).
worked in the Production Modeling group with Jayant Kalagnanam and Andrew Davenport