Lijun Sun
Ph.D., P.Eng., William Dawson Scholar
Professor Sun’s research centers on the area of urban computing and smart transportation, developing innovative methodologies and applications to address efficiency, resilience, and sustainability issues in urban transportation systems. In particular, he is interested in integrating advances in mobile sensing and machine learning into human mobility modeling, agent-based simulation, and intelligent transportation systems to explore how big data, artificial intelligence, and cyber-physical systems could benefit urban life and help build smart cities. His work has been featured in popular media outlets, including Wired, Citylab, Scientific American, and MIT Technology Review.
- Ph.D., Civil Engineering (Transportation), National University of Singapore, Singapore (2015)
- B.Eng., Civil Engineering, Tsinghua University, China (2011)
Transportation Engineering
- Alabdulkareem, A., Frank, M.R., Sun, L., AlShebli, B., Hidalgo, C., Rahwan, I., 2018. Unpacking the polarization of workplace skills. Science Advances 4(7), eaao6030.
- Sun, L., Erath, A., Cai, M., 2018. A hierarchical mixture modeling framework for population synthesis. Transportation Research Part B: Methodological 114, 199–212.
- Frank, M.R., Obradovich, N., Sun, L., Woon, W.L., LeVeck, B.L., Rahwan, I., 2018. Detecting reciprocity at a global scale. Science Advances 4(1), eaao5348.
- Sun, L., Yin, Y., 2017. Discovering themes and trends in transportation research using topic modeling. Transportation Research Part C: Emerging Technologies 77, 49–66.
- Sun, L., Axhausen, K.W., 2016. Understanding urban mobility patterns with a probabilistic tensor factorization framework. Transportation Research Part B: Methodological 91, 511–524.
- Sun, L., Lu, Y., Jin, J.G., Lee, D.-H., Axhausen, K.W., 2015. An integrated Bayesian approach for passenger flow assignment in metro networks. Transportation Research Part C: Emerging Technologies 52, 116–131.
- Sun, L., Erath, A., 2015. A Bayesian network approach for population synthesis. Transportation Research Part C: Emerging Technologies 61, 49–62.
- Sun, L., Jin, J.G., Axhausen, K.W., Lee, D.-H., Cebrian, M., 2015. Quantifying long-term evolution of intra-urban spatial interactions. Journal of The Royal Society Interface 12, 20141089.
- Jin, J.G., Tang, L.C., Sun, L., Lee, D.-H., 2014. Enhancing metro network resilience via localized integration with bus services. Transportation Research Part E: Logistics and Transportation Review 63, 17–30.
- Sun, L., Axhausen, K.W., Lee, D.-H., Cebrian, M., 2014. Efficient detection of contagious outbreaks in massive metropolitan encounter networks. Scientific Reports 4, 5099.
- Sun, L., Jin, J.G., Lee, D.-H., Axhausen, K.W., Erath, A., 2014. Demand-driven timetable design for metro services. Transportation Research Part C: Emerging Technologies 46, 284–299.
- Sun, L., Axhausen, K.W., Lee, D.-H., Huang, X., 2013. Understanding metropolitan patterns of daily encounters. Proceedings of the National Academy of Sciences of the United States of America 110, 13774–9.
- Urban computing & smart cities
- Machine learning for mobility modeling
- Intelligent transportation systems
- Spatio-temporal traffic state modeling/predication
- Infrastructure resilience
- Data-driven urban/transportation systems modeling
- Human mobility and travel behavior
- Agent-based modeling and simulation
- Public transportation operation & planning
- Postdoctoral Associate, MIT Media Lab, Massachusetts Institute of Technology, USA (2015-2017)
- Researcher Fellow, Future Cities Laboratory, Singapore-ETH Center, Singapore (2014-2015)
- Visiting Research, National ICT Australia (CSIRO’s Data61 now), Australia (2015-2015)