Educational background

●1998–2002, Ph.D. in Engineering Thermophysics, Tsinghua University
●2012–2015, M.S. in Applied Psychology, Peking University
●1995–1998, M.S. in Engineering Thermophysics, Shandong University
●1991–1995, B.S. in Thermal Engineering, Shandong University

Experience

●Nov. 2023–Present, Faculty, Institute for Public Safety Research, School of Safety Science, Tsinghua University
●2004–2023, Faculty, Institute for Public Safety Research, Department of Engineering Physics, Tsinghua University
●2011–2012, Visiting Scholar, John F. Kennedy School of Government, Harvard University
●2002–2004, Postdoctoral Fellow, Department of Engineering Mechanics, Tsinghua University

Teaching work

●Since 2012: "Introduction to Public Safety Science" (Undergraduate course)
●Since 2017: "Physics in Engineering Applications and Engineering Practice in Physics Exploration" (Undergraduate course)
●2010–2016: "Introduction to Public Safety Science" (Postgraduate course)
●2015–2017: "Case-Based Reasoning and Its Application in Emergency Decision-Making" (Postgraduate course)
●Since 2018: "Scenario Simulation Methods" (Postgraduate course)
●Since 2024: "Artificial Intelligence and Public Safety" (Postgraduate course)

Areas of Research Interests

The researches focuse on modeling, computation, and high-precision prediction of disaster and accident dynamics through the integration of dynamics and artificial intelligence. His work also explores human behavior and human factors analysis in disaster scenarios, involving multi-source heterogeneous data fusion, trustworthy data interaction technologies, and the construction and application of knowledge graphs. These techniques support quantitative risk assessment, emergency planning, and fine-grained decision support.

Research Status

National Natural Science Foundation of China (PI):
●2007–2009: Risk assessment methods for spatiotemporal coupling of mobile hazards with multiple factors
●2014–2015: Simulation and decision support for large-scale emergency evacuation in urban regions
●2017–2019: Research on cross-scale modeling and decision-making paradigms driven by big data
●2017–2020: Research on model integration management methods for emergency decision support
●2020–2025: Emergency traffic evacuation decision support methods based on driving behavior modeling and simulation
National Key R&D Program Projects (PI):
●2018–2021: Technologies for multi-source heterogeneous data acquisition, spatiotemporal fusion analysis, and integrated sharing in community risk management
●2022–2025: Theories, methods, and standards for multi-dimensional risk prevention and comprehensive response to biological events
Strategic Research Projects of the Chinese Academy of Engineering (PI):
●2024–2025: Strategic research on the development of safety and resilience technologies for urban and social systems under extreme disasters
●2025–2026: Strategic research on smart emergency response and regional collaborative resilient safety development in Xiong'an New Area

Academic Achievement

Selected Representative Publications:
1.WANG R P, GU Y, LIU Y. A simple yet effective multivariate long sequence wind speed prediction model for urban blocks with spatio-temporal feature embedding[J]. Energy, 2025, 330: 136725. DOI: 10.1016/j.energy.2025.136725
2.GU Y, LIU Y, CHEN Y Q, et al. Near real-time warning for urban tree destruction under coupled wind and rain loads: Prediction framework and case study[J]. International Journal of Disaster Risk Reduction, 2025: 105663. DOI: 10.1016/j.ijdrr.2025.105663
3.WANG Q, LIU Y. Blockchain empowered dynamic access control for secure data sharing in collaborative emergency management[J]. Information Processing & Management, 2025, 62(3): 103960. DOI: 10.1016/j.ipm.2024.103960
4.WANG R P, GAO H, LIU Y. A data fusion-based method for pedestrian detection and flow statistics across different crowd densities[J]. Journal of Safety Science and Resilience, 2025, 6(1): 105-113. DOI: 10.1016/j.jnlssr.2024.07.004
5.LIU Y, GU Y, ZHANG H. Seismic risk assessment and damage analysis: Emerging trends and new developments[J]. Journal of Safety Science and Resilience, 2024, 5(3): 365-381. DOI: 10.1016/j.jnlssr.2024.04.005
6.LIU Y, WANG R P, GU Y, et al. Physics-inspired and data-driven two-stage deep learning approach for wind field reconstruction with experimental validation[J]. Energy, 2024, 298: 131230. DOI: 10.1016/j.energy.2024.131230
7.WANG G Q, XING H, CHEN Y Q, LIU Y. A dynamic exploratory hybrid modelling framework for simulating complex and uncertain system[J]. Journal of Safety Science and Resilience, 2024, 5(2): 167-178. DOI: 10.1016/j.jnlssr.2024.03.001
8.GAO H, LIU Y. Improving real-time driver distraction detection via constrained attention mechanism[J]. Engineering Applications of Artificial Intelligence, 2024, 128: 107408. DOI: 10.1016/j.engappai.2023.107408
9.GAO H, HU M T, LIU Y. Learning Driver-Irrelevant Features for Generalizable Driver Behavior Recognition[J]. IEEE Transactions on Intelligent Transportation Systems, 2024, 25(10): 14115-14127. DOI: 10.1109/TITS.2024.3396640
10.WANG Q, LIU Y. Blockchain for public safety: A survey of techniques and applications[J]. Journal of Safety Science and Resilience, 2023, 4(4): 389-395. DOI: 10.1016/j.jnlssr.2023.09.001
11.QIAN J, LIU Y. Quantitative scenario construction of typical disasters driven by ontology data[J]. Journal of Safety Science and Resilience, 2023, 4(2): 159-166. DOI: 10.1016/j.jnlssr.2022.12.002
12.XING H, LIU Y. Graph attention network for Car‐Following Model under game between desired and real state[J]. IET Intelligent Transport Systems, 2022, 16(6): 800-812. DOI: 10.1049/itr2.12175

Academic part-time job

Editorial Board Member, 《Journal of Safety Science and Resilience》

Rewards and Honors