2020, Ph.D., Department of Industrial and Operations Engineering, University of Michigan
2015, Master of Science, Division of Systems Engineering, Boston University
2012, Bachelor of Engineering, School of Landscape Architecture, Beijing Forestry University
International Experience
2020, Postdoctoral Research Associate, Carnegie Mellon University
2018-2020, Visiting Student, Columbia University
Research Interests
Monte Carlo Simulation
Stochastic and Robust Optimization
Rare-Event Simulation
Selected Publications
Papers
Hong, J. L., Huang, Z. * and Lam, H., Learning-based robust optimization: procedures and statistical guarantees, Management Science, , 2021, 67(6): 3447-3467.
Huang, Z. *, Zhao, D., Lam, H., and LeBlanc, D., Accelerated evaluation of automated vehicles via importance sampling under piecewise mixture distributions, IEEE Transactions on Intelligent Transportation Systems, vol. 19, no. 9, pp. 2845-2855, 2018.
Bai, Y., Huang, Z. *, Lam, H., A distributionally robust optimization approach to the NASA Langley uncertainty quantification challenge, Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference(ESREL2020 PSAM15), 2020.
Huang, Z. *, Arief, M., Lam, H., Zhao, D., Evaluation uncertainty in data driven self-driving testing, Proceedings of the IEEE 22nd Inter-national Intelligent Transportation Systems Conference (ITSC), 2019.
Huang, Z. *, Lam, H., On the impacts of tail model uncertainty in rare-event estimation, Proceedings of the Winter Simulation Conference (WSC), 2019.
Luo, Q., Huang, Z. *, Lam, H., Dynamic congestion pricing for ride sourcing traffic: a simulation optimization approach, Proceedings of the Winter Simulation Conference (WSC), 2019.
Huang, Z. *, Lam, H., Zhao, D., Designing importance samplers to simulate machine learning predictors via optimization, Proceedings of the Winter Simulation Conference (WSC), 2018.
Huang, Z. *, Lam, H., Zhao, D., Rare-event simulation without structural information: a learning-based approach, Proceedings of the Winter Simulation Conference (WSC), 2018.
Huang, Z. *, Arief, M., Lam, H., Zhao, D., Synthesis of different autonomous vehicles test approaches, Proceedings of the IEEE 21thInternational Intelligent Transportation Systems Conference (ITSC),2018.
Huang, Z. *, Guo, Y, Lam, H., Zhao, D., A versatile approach for the evaluation and testing of automated vehicles based on kernel methods, Proceedings of the American Control Conference (ACC), 2018.
Huang, Z. *, Lam, H., Zhao, D., Sequential experimentation to efficiently test automated vehicles, Proceedings of the Winter Simulation Conference (WSC), 2017.
Huang, Z. *, Lam, H., Zhao, D., Towards affordable on-track testing for autonomous vehicle - a kriging-based statistical approach, Proceedings of the IEEE 20th International Intelligent Transportation Systems Conference (ITSC), 2017.
Huang, Z. *, Lam, H., Zhao, D., An accelerated testing approach for automated vehicles with background traffic described by joint distributions, Proceedings of the IEEE 20th International Intelligent Transportation Systems Conference (ITSC), 2017.
Huang, Z. *, Lam, H., Zhao, D., Evaluation of automated vehicles in the frontal cut-in scenario - an enhanced approach using piecewise mixture model, Proceedings of the International Conference on Robotics and Automation (ICRA), 2017.
Hong, J. L., Huang, Z. *, and Lam, H., Approximating data-driven joint chance-constrained programs via uncertainty set construction, Proceedings of the Winter Simulation Conference (WSC), 2016.