Publications
📄 Publications
I have authored:
- 1 book chapter
- 50+ peer-reviewed journal articles
- 30+ conference papers and presentations
These works span a wide range of topics including:
- Travel demand modeling
- Travel behavior analysis
- Agent-based modeling
- Transportation big data
- Advanced econometrics
- Transportation and public health
The most cited and representative studies are listed below.
A complete publication list is available upon request.
📚 You can also explore my full portfolio on
my Google Scholar profile.
✍️ Selected Publications
Published in Proceedings of National Academy of Sciences (PNAS), 2020
U.S. county level human mobility were measured from individual level passively collected data and linked to a panel data model for modeling and predicting SARS-CoV-2 pandemic in the U.S.
Recommended citation: Xiong, et. al., (2020). "Mobile device data reveal the dynamics in a positive relationship between human mobility and COVID-19 infections." Proceedings of National Academy of Sciences (PNAS). 117 (44) 27087-27089. https://www.pnas.org/doi/full/10.1073/pnas.2010836117
Published in Transportation Research Part C: Emerging Technologies, 2020
This paper studied an integrated incentivization mechanism that realisticly models subjects` behavioral response to different types of incentives and optimizes the incentive allocation with a control optimizer.
Recommended citation: Xiong et al., (2010). "An integrated and personalized traveler information and incentive scheme for energy efficient mobility systems." Transportation Research Part C: Emerging Technologies. 113, 57-73. https://www.sciencedirect.com/science/article/pii/S0968090X18317364
Published in Transportation Science, 2018
This paper extends the dynamically formulated hidden Markov models to a high-order hidden Markov model (HO-HMM) formulation. In the HO-HMM, the Markovian assumption that the future states (interpreted as the states of preferences or attitudes) depend only on the current state has been relaxed. Instead, the HO-HMM generalizes that the future states will depend on a number of states occurring beforehand.
Recommended citation: Xiong et. al., (2018). "A high-order hidden Markov model and its applications for dynamic car ownership analysis." Transportation Science. 52 (6), 1365-1375. https://pubsonline.informs.org/doi/abs/10.1287/trsc.2017.0792