Stochastic Optimization: data-efficient algorithms to solve stochastic optimization problems; adaptive data sampling techniques for fast learning
Applied Probability: interface of queuing theory with optimization, e.g. optimal capacity planning; large deviations principles
Simulation and Statistics: distributionally-robust estimation; efficient risk analysis; efficient online estimation of tail measures; Bayesian forecasting methods, dynamic linear models; input modeling
Machine Learning: data-efficient online methods for applications that consume large data-streams, e.g. fast inference from EEG / fMRI, voice recognition etc.
Smarter Energy: market mechanism design for Smart Grids; unit commitment, economic dispatching, risk and contingency analysis under uncertainty
Smarter Clouds: large-deviations theory to model computation loads; optimal dynamic balancing of loads; online metrics for SLAs
Supply-Chain: optimal portfolio/assortment management for complex bills-of-material; optimal cross-shipment strategies