Assistant Professor, University of Minnesota - Twin Cities
2 papers at NeurIPS 2025
Creating safe and reward maximization policies from offline data via min-max optimization formulation and solving it using no-regret algorithms
We introduce BO4Mob, a new Bayesian Optimization (BO) benchmark framework for origin-destination (OD) travel demand estimation as high-dimensional urban mobility problem.
