Greetings! My name is Chenfeng Xiong.

I am an Assistant Research Professor at the Department of Civil and Environmental Engineering, University of Maryland, College Park, and am an affiliated Assistant Professor at the Shock Trauma Center, School of Medicine, University of Maryland, Baltimore. I earned my Ph.D. in Transportation Engineering from the University of Maryland in 2015. I earned M.A. in Economics and M.S. in Transportation Engineering from the University of Maryland in 2013 and 2011, respectively. My Bachelor's degree with a major in Civil Engineering was awarded at Tsinghua University, Beijing in June 2009. I am interested in understanding the fundamentals of transportation systems, including travelers' choices, mobility, safety, health, and economics. More about me can be found in this personal webpage.

Curriculum Vitae [Download] Google Site [Click Here]

For Perspective Students

PhD positions

I am constantly looking for motivated PhD students who are extremely excited about exploring data-driven modeling, simulations, and statistical methods to address transportation and mobility related research questions. If you are one, please send an email with your CV to my email address: cxiong at umd dot edu.

High-school and undergraduate internships

I welcome talented and motivated high-school students and undergraduate students to join my group for summer and regular-semester internships, experiencing research and university life and working with senior group members together on critical, interesting, and sometimes challenging research problems. Send in your application by completing this form.


Ph.D., Transportation Engineering, University of Maryland, 2015

M.A., Economics, University of Maryland, 2013

M.S., Civil and Environmental Engineering, University of Maryland, 2011

B.S., Civil Engineering, Tsinghua University, 2009


Transportation Systems

I work on transportation systems models and simulation to replicate the real-world human mobility and adaptations, and predict future landscape of the transportation systems and beyond.

Data-Driven Modeling

Big data and data-driven approach can be applied to solve often complex problems. I am interested in advanced mathematical and statistical methods to extract empirical evidences for problem-solving.

Interdisciplinary Perspectives

Mobility is a major pillar of people's everyday life. I am interested in exploring multidisciplinary topics cutting across transportation economics, safety, and health that are fundamental to quality of life.

Funded Projects

[1] USDOT: A Data-Driven Safety Dashboard Assessing Maryland Statewide Density Exposure of Pedestrians, Bicycles, and E-Scooters. 2020-2021. Role: PI.

[2] USDOT Federal Highway Administration: Deployment of Personalized and Dynamic Travel Demand Management Technology in the Washington, DC-Baltimore, MD-Richmond, VA Megaregion. 2020-2023. Role: PI.

[3] Maryland DOT: Implementation and Operations of incenTrip Smartphone Technology and Commuter Choice Calculator in Maryland. 2019-2022. Role: PI.

[4] Maryland DOT State Highway Administration: Identification of Best Practice Metrics for Varying Levels of Traffic Operations Analysis. 2019-2021. Role: Co-PI.

[5] Maryland DOT State Highway Administration: Big Data for Safety: Improving Pedestrian and Biker Safety with Integrated Crash and Mobile Device Data Analysis. 2019-2019. Role: PI.

[6] Maryland DOT State Highway Administration: Analyzing Travelers' Response to Different Active Traffic Management (ATM) Technologies. 2016-2018. Role: PI.

[7] National Science Foundation: Transit Network Disruption, Service Reliability, and Travel Behavior. 2017-2018. Role: Co-PI.


Published over 50 peer-reviewed journal articles (Full list available upon request).

Book Chapter

[1] Xiong, C., X. Chen, and L. Zhang. (2015). Multidimensional travel decision-making: Descriptive behavioral theory and agent-based models. In Rasouli S., Timmermans, H.J.P. Eds, Bounded Rational Choice Behaviour: Applications in Transport (2015): 213-230. 2015. Emerald Group Publishing. [Post-Print]

Most Recent Journal Articles

[1] C. Xiong, Yang, D., et al., (2020). Measuring and enhancing the transferability of hidden Markov models for dynamic travel behavioral analysis. Transportation. 47 (2), 585-605. [DOI].

[2] C. Xiong, Shahabi, M., et al., (2020). An integrated and personalized traveler information and incentive scheme for energy efficient mobility systems. Transportation Research Part C: Emerging Technologies. 113, 57-73. [DOI].

[3] C. Xiong, Hu, S., et al., (2020). Mobile device location data reveal human mobility response to state-level stay-at-home orders during the COVID-19 pandemic in the USA. Journal of the Royal Society Interface 17 (173), 20200344. [DOI].

[4] C. Xiong, Hu, S., et al., (2020). Mobile device data reveal the dynamics in a positive relationship between human mobility and COVID-19 infections. Proceedings of the National Academy of Sciences (PNAS). 117 (44), 27087-27089. [DOI].

[5] Hu, S., C. Xiong, et al., (2021). Examining spatiotemporal changing patterns of bike-sharing usage during COVID-19 pandemic. Journal of Transport Geography 91, 102997. [DOI].

[6] Hu, S., C. Xiong, et al., (2021). A big-data driven approach to analyzing and modeling human mobility trend under non-pharmaceutical interventions during COVID-19 pandemic. Transportation Research Part C: Emerging Technologies 124, 102955. [DOI].

[7] C. Xiong, Yang, X., et al., (2021). An integrated modeling framework for active traffic management and its applications in the Washington, DC area. Journal of Intelligent Transportation Systems, In Press. [DOI].

[8] C. Xiong, Darzi, A., et al., (2021). A data-driven analytical framework of estimating multimodal travel demand patterns using mobile device location data, arXiv Preprint. [arXiv:2012.04776].

Web Counter Hits