Welcome!
About me
I am a professor in Transportation and Infrastructure Systems Engineering, Lyles School of Civil Engineering, Purdue University.
Address: HAMP G167D, 550 Stadium Mall Drive, West Lafayette, IN 47907-2051
Phone: (765) 494-2296
Fax: (765) 494-7996
Selected papers
- Xue, J., Jiang, N., Liang, S., Pang, Q., Yabe, T., Ukkusuri, S.V., & Ma, J. (2022). Quantifying spatial homogeneity of urban road networks via graph neural networks. Nature Machine Intelligence, 4, pp. 246-257.
- Yabe, T., Rao, P.S.C., Ukkusuri, S.V., & Cutter, S. (2022). Towards data driven, dynamical complex systems approaches to disaster resilience. Proceedings of the National Academy of Sciences, Vol. 119 (8),e2111997119.
- Qian, X., Zhang, W., Ukkusuri, S.V., & Yang, C. (2017). Optimal Assignment and Incentive Design in the taxi group ride problem. Transportation Research Part B (Methodological) , Vol. 203, pp. 208-226.
- Lei, Z., Xue, J., Chen, X., Qian, X., Saumya, C., He, M., … & Ukkusuri, S. V. (2024). METS-R SIM: A simulator for Multi-modal Energy-optimal Trip Scheduling in Real-time with shared autonomous electric vehicles. Simulation Modelling Practice and Theory, 132, 102898.
- Hasan, S., Schneider, C., Ukkusuri, S.V., & Gonzalez, M. (2013). Spatiotemporal patterns of urban human mobility. Journal of Statistical Physics. Vol. 151, Issue 1-2, pp. 304-318.
- Ukkusuri, S. V., Tom,V. M., & Waller, S. T. (2007). Robust transportation network design under demand uncertainty. Computer Aided Civil and Infrastructure Engineering. Vol. 22, pp. 9-21.
- Jie, B., Liu, P., & Ukkusuri, S.V. (2019). A Spatiotemporal Deep Learning Approach for Citywide Short-Term Crash Risk Prediction with Multi-source Data. Accident Analysis and Prevention, Vol. 122, pp. 239-254.
- Hasan, S., & Ukkusuri, S.V. (2013). Understanding Urban Human Activity and Mobility Patterns Using Large-Scale Location-Based Data from Online Social Media. In Proceedings of 92nd Transportation Research Board Meeting, National Academies (Washington D.C.).
- Yabe, T., Tsubouchi, K., Fujiwara, N., Sekimoto, Y., & Ukkusuri, S. V. (2020). Understanding post-disaster population recovery patterns. Journal of the Royal Society Interface, 17(163), 20190532.
- Qian, X., Lei, T., Xue, J., Lei, Z., & Ukkusuri, S.V. (2020). Impact of transportation network companies on urban congestion: Evidence from large-scale trajectory data. Sustainable Cities and Society, Vol. 55, 102053.
- Zhan, X., Ukkusuri, S.V., & Rao, P.S.R.C. (2017). Dynamics of functional failures and recovery in complex road networks. Physical Review E, Vol. 96(5), 052301.
- Ukkusuri, S. V., Park, S. U., Mittal, S., Chapman, L., Manoli, G., Santos, A., … & Romero, N. (2024). “We need to prepare our transport systems for heatwaves—here’s how”. Nature, 632(8024), 253-256.
News
August 2024: New comment paper “We need to prepare our transport systems for heatwaves—here’s how” has been published on Nature.
May 2024: Congratulations to Jiawei Xue, Xiaowei Chen, SangUng Park, and Mithun Debnath on successfully defending their theses!
May 2024: New paper “A physics-informed machine learning for generalized bathtub model in large-scale urban networks” has been published on Transportation Research Part C.
Mar. 2024: New paper “Modeling the influence of charging cost on electric ride-hailing vehicles” has been published on Transportation Research Part C.
Jan. 2024: New paper “Comparison of home detection algorithms using smartphone GPS data” has been published on EPJ Data Science.
Jan. 2024: New paper “METS-R SIM: A simulator for Multi-modal Energy-optimal Trip Scheduling in Real-time with shared autonomous electric vehicles” has been published on Simulation Modeling Practice and Theory.
Nov. 2023: New paper “Scalable reinforcement learning approaches for dynamic pricing in ride-hailing systems” has been published on Transportation Research Part B.
Sept. 2023: New paper “Mapping sidewalks on a neighborhood scale from street view images” has been published on Environment and Planning B: Urban Analytics and City Science.
Nov. 2022: New paper“Modeling the dynamics and spatial heterogeneity of city growth” has been published on npj Urban Sustainability.
Oct. 2022: New paper “Spatial structure of city population growth” has been published on Nature Communications.
May 2022: New paper “Progression of hurricane evacuation-related dynamic decision-making with information processing” has been published on Transportation Research Part D.
Mar. 2022: New paper “Quantifying the spatial homogeneity of urban road networks via graph neural networks” has been published on Nature Machine Intelligence.
Feb. 2022: New paper “Toward data-driven, dynamical complex systems approaches to disaster resilience” is published on PNAS.
Nov. 2021: Dr. Washim Mondal received the best paper award in the Cooperative AI workshop at NeurIPS 2021 for his work “On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)”.
June 2021: Congratulations on the graduation of Dr. Hemant Gehlot!
July 2020: New paper “Efficient proactive vehicle relocation for on-demand mobility service with recurrent neural networks” is now online.
Apr. 2020: Our new paper “Impact of transportation network companies on urban congestion: Evidence from large-scale trajectory data” has been published on Sustainable Cities and Society.
Mar. 2019: New paper “A-RESCUE 2.0: A High-Fidelity, Parallel, Agent-Based Evacuation Simulator” is now online.
Dec. 2018: Congratulations on the graduation of Dr. Xinwu Qian and Dr. Wenbo Zhang!
Nov. 2018: New paper “User equilibrium with a policy-based link transmission model for stochastic time-dependent traffic networks” is now online.
Nov. 2018: New paper: “Joint modeling of evacuation departure and travel times in hurricanes” is now online.
Oct. 2018: Our work in the recent research foundation news “A little help from your friends is key to natural disaster recovery, Purdue research study suggests”.
Oct. 2018: New paper “A spatiotemporal deep learning approach for citywide short-term crash risk prediction with multi-source data” is now online.
