Li Jin

  • Assistant Professor


Li Jin

Li Jin is an Assistant Professor in the Tandon School of Engineering at New York University. His research focuses on developing resilient control algorithms for cyber-physical systems with guarantees on efficiency in nominal settings, robustness against random perturbations, and survivability under strategic disruptions. The theoretical foundation of his work includes stochastic process and control theory. Specific applications of his work include connected and autonomous vehicles, automatic traffic control, air transportation, and gas network. He is a recipient of the Ho-Ching and Hang-Ching Fund Award and Schoettler Scholarship Fund.

We are recruiting graduate/undergraduate students for Ph.D., term projects, and summer research internship. Students with related engineering/math/CS background are welcome to contact us at

Research Interests: Smart cities, Traffic control, Connected & autonomous vehicles, Cyber-physical systems

Ph.D., Transportation, Massachusetts Institute of Technology, 2018

M.S., Mechanical Engineering, Purdue University, 2012

B.Eng., Mechanical Engineering, Shanghai Jiao Tong University, 2011

Integration of vehicle platooning in highways with mixed traffic

Vehicle platooning

We investigate how to design vehicle platooning operations for maximal efficiency and environmental benefits. We develop multi-class fluid queuing models for highways with mixed autonomy and focus on the interaction between CAVs and ordinary vehicles. Our performance metrics include travel time, throughput, and safety level.

Related papers:

  • Jin, L., Čičić, M., Amin, S., & Johansson, K. H., Coordinated control of vehicle platoons in Mixed Traffic: A Fluid Model-based approach, working paper
  • Jin, L. & Amin, S., (2018) Stability of fluid queueing systems with parallel servers and stochastic capacities, IEEE Transactions on Automatic Control pdf
  • Jin, L., Čičić, M., Amin, S., & Johansson, K. H., (2018) Modeling impact of vehicle platooning on highway congestion: A fluid queuing approach, 21st ACM International Conference on Hybrid Systems: Computation and Control pdf

Automatic highway control under stochastic perturbations

Ramp metering

We design feedback ramp control policies that improves throughput under stochastic capacity disruptions. We come to a rather surprising conclusion: prioritizing the link with a higher utilization ratio is not necessarily optimal; instead, the link with a smaller capacity-demand margin should be prioritized. We are also evaluating our results via simulation of calibrated models.

Related papers:

  • Jin, L., Kurzhanskiy, A., & Amin, S., Throughput-Improving Control of Highways Facing Stochastic Perturbations, preprint, pdf
  • Jin, L. & Amin, S., Analysis of a stochastic switching model of freeway traffic incidents, to appear in IEEE Transactions on Automatic Control pdf
  • Jin, L. & Amin, S. (2017) Calibration of a macroscopic traffic flow model with stochastic saturation rates, Transportation Research Board 88th Annual Meeting pdf

Cyber-physical disruptions of transportation networks


We model and analyze the impact of cyber vulnerabilities on smart highways. We consider the resource allocation problem for recovery processes and adaptively react to detected attacks. We also study the incentives of strategic misbehavior by individual vehicles who can exploit the security vulnerabilities in V2I communications and impact the highway operations.

Related papers:

  • Wu, M., Jin, L., Amin, S., & Jaillet, P., (2018) Signaling game-based misbehavior inspection in V2I-enabled highway operations, The 57th IEEE Conference on Decision and Control pdf

Stochastic models and methods for transportation systems, Spring 2019

Current Projects, Research Labs, and Groups