Mengyu Guo, research assistant professor, PhD degree from Tsinghua University. Research interests include modelling, simulation and optimal control of complex intelligent systems in manufacturing and service applications; Enterprise architecture methodology in domains such as supply chain management.

Industrial Engineering Department at Tsinghua University，PhD🫃🏼，2014

University of Illinois at Urbana and Champaign，Visiting Scholar，2012-2013

Mechanical Engineering School at Southeast University⌨️，B.S.🙋🏼‍♂️，2009

2020.6-Present, research Assistant professor, Industrial Engineering Department at Tsinghua University

2018.7-2019.10, University of California at Berkeley, Postdoctoral Researcher

2017.7-2018.7, University of Illinois at Urbana and Champaign, Postdoctoral Researcher

2014.7-2016.7, Research and Development Center (AVIC), Engineer and Project Manager

Systems Engineering and Systems of Systems Engineering

Enterprise Architecture

Machine Learning (Deep reinforcement learning)

Intelligent Transportation

Healthcare

Supply chain management

1. Wang, H., Yuan, S., Guo, M.*, Li, X., & Lan, W. (2021). A deep reinforcement learning-based approach for autonomous driving in highway on-ramp merge. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 0954407021999480. https://doi.org/10.1177/0954407021999480

2. Wang, H., Yuan, S., Guo, M.*, Chan, C. Y., Li, X., & Lan, W. (2020). Tactical driving decisions of unmanned ground vehicles in complex highway environments: A deep reinforcement learning approach. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. https://doi.org/10.1177/0954407019898009

3. Guo, M., & Wang, S. (2020). Quantum Computing for Solving Spatial Optimization Problems. In High Performance Computing for Geospatial Applications (pp. 97–113). https://doi.org/10.1007/978-3-030-47998-5_6

4. Guo, M., Wang, P., Chan, C., & Askary, S. (2019). A Reinforcement Learning Approach for Intelligent Traffic Signal Control at Urban Intersections. In 2019 IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 4242–4247).

5. Raubal, M., Wang, S., Guo, M., Jonietz, D., & Kiefer, P. (Eds.). (2018). Spatial Big Data and Machine Learning in GIScience. In Workshop at GIScience 2018.

6. Guo, M., Wu, S., Li, B., Song, J., & Rong, Y. (2016). Integrated scheduling of elective surgeries and surgical nurses for operating room suites. Flexible Services and Manufacturing Journal, 28(1–2), 166–181.

7. Guo, M., Wu, S., Li, B., & Rong, Y. (2014). Maximizing the efficiency of use of nurses under uncertain surgery durations: A case study. Computers and Industrial Engineering, 78, 313–319.

8. Guo, M., Li, B., Zhang, Z., Wu, S., & Song, J. (2013). Efficiency evaluation for allocating community-based health services. Computers & Industrial Engineering, 65(3), 395–401. https://doi.org/10.1016/j.cie.2013.03.008

9. Guo, M., Li, B., Wu, S., & Song, J. (2011). Effectiveness of referral incentive policy: Exploring using queuing network model with blocking. In 8th International Conference on Service Systems and Service Management - Proceedings of ICSSSM’11.

Chapter representative of Beijing Chapter, INCOSE