• Best Paper Award Runner-up (Theoretical Track), INFORMS Decision Mining and Decision Analytics (DMDA) Workshop, 2023.
• Best Theoretical Paper Award, Winter Simulation Conference, 2022, for our paper “Fixed Budget Ranking and Selection under Streaming Input Data”.
• INFORMS Outstanding Simulation Publication Award, 2020, for our paper “A Bayesian Risk Approach to Data-driven Stochastic Optimization: Formulations and Asymptotics“. (This award recognizes exceptional contributions to the simulation literature in the form of articles, books, book chapters and monographs, copyrighted in the past three years.)
• I-SIM Best OR/MS-focused Student Paper, Winter Simulation Conference, 2020, awarded to Tianyi Liu for our paper “Simulation Optimization by Reusing Past Replicaitons: Don’t be afraid of Dependence“.
• Fouts Family Early Career Professorship, Georgia Tech, 2016-2019.
• Finalist for Best Paper Award, Journal of Global Optimization, 2016.
• NSF CAREER Award, 2014.
• AFOSR Young Investigator Award, 2012.
• Outstanding Reviewer, IEEE Transactions on Automatic Control, 2010, 2015.
• Best Theoretical Paper Award, Winter Simulation Conference, 2009, for our paper “A Numerical Method for Financial Decision Problems under Stochastic Volatility“.
• Dean’s Doctoral Research Award, University of Maryland, College Park, 2009.
• ECE Distinguished Dissertation Award, University of Maryland, College Park, 2009.
• Finalist for the Best Student Paper Award, Winter Simulation Conference, 2008.
• NSF Award for Cyber Infrastructure Experiences for Graduate Students (CIEG) program, 2007.
• Chu Kochen Scholarship, highest honors in Zhejiang University, 2004.
• Outstanding Winner & INFORMS Outstanding Paper, Mathematical Contest in Modeling, 2003.

Grants

• “Bayesian Risk-Sensitive and Distributionally-Robust Optimization”, NSF EAGER (through AI4OPT), Principal Investigator (with Alexander Shapiro), 2022-2023.
• “Bayesian Risk-averse and Distributionally-robust Approaches to Data-driven Stochastic Optimization”, sponsored by AFOSR, Principal Investigator (with Alexander Shapiro), 2022 – 2025.
• “Addressing Input Model Uncertainty in Stochastic Simulation: From Quantification to Optimization”, sponsored by National Science Foundation, Principal Investigator, 2021 – 2024.
• “Decentralized Bayesian Multi-Agent Multi-Target Search, Localization, and Tracking”, sponsored by AFOSR, Principal Investigator of GT (with Peter Frazier, Aly Megahed, Fumin Zhang), 2019 – 2022.
• “Data-driven Courier Scheduling for Express Services”, sponsored by SF Express Inc., Co-Principal Investigator (with George Lan, Alexander Shapiro, Yao Xie), 2017 – 2018.
• “CAREER: Optimization and Sampling in Stochastic Simulation”, sponsored by the National Science Foundation, Principal Investigator, 2015 – 2020.
• “Dynamic Decision Making under Uncertainty and Partial Information”, sponsored by the AFOSR Young Investigator Program, Principal Investigator, 2012-2017.
• “Collaborative Research: A New Paradigm for Simulation Optimization: Marriage between Expectation-Maximization and Model-Based Optimization”, sponsored by the National Science Foundation, Principal Investigator of UIUC (with Jiaqiao Hu), 09/2011 – 08/2014.
• “A New Monte Carlo Framework for Global Optimization”, sponsored by UIUC Research Board, Principal Investigator, 2011-2012.
• “Particle Filtering for Stochastic Control and Global Optimization”, sponsored by the National Science Foundation, Principal Investigator of UIUC (with Steve Marcus, Michael Fu), 09/2009-08/2012.