Li Jin



PhD Candidate in Transportation

Massachusetts Institute of Technology

Research area: control of unreliable transportation networks, stochastic processes, probability theory, and network optimization.

Expected to graduate in 2018


Address: 77 Massachusetts Ave., Rm. 1-253C.


About Me

I am a PhD in Transportation candidate at the Massachusetts Institute of Technology. I am working with Prof. S. Amin on resilient control of transportation networks. I was born in Nanjing, China, to a couple of state-owned enterprise employees. I grew up in Nanjing, and went to college in Shanghai. I came to the United States when I was a senior student. My hobbies are history, linguistics, literature, and soccer. My favorite historian, linguist, novelist, and soccer player are René Grousset, Yuen Ren Chao (元任), Stephan Zweig, and Robert Lewandowski, respectively.

More information about my academic/professional experience is available in my Curriculum Vitae.


·      Ph.D. Candidate in Transportation, Massachusetts Institute of Technology, Cambridge, MA.

o   Advisor: Saurabh Amin

o   Thesis committee: Saurabh Amin, Hamsa Balakrishnan, Demos Teneketzis, Nigel H. M. Wilson (chair)

·      Master of Science in Mechanical Engineering, Purdue University, West Lafayette, IN, 2012.

o   Advisor: Dengfeng Sun

·      Bachelor of Engineering in Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China, 2011.


My research area is resilient operation of transportation systems. My research is motivated by the prevalence of disturbances in transportation systems, such as crashes, adverse weather, and traffic signal malfunction. My modeling approach is to use stochastic processes to describe the occurrence and clearance of disturbances, and to use perturbed flow/queueing dynamics to characterize the congestion induced by disturbances. I am particularly interested in designing traffic management strategies that enable the system to survive disturbances. My works involve ideas from stochastic process, network optimization, and dynamic control.

More information about my research is available in my research statement and research presentation.


·      Jin, L. & Amin, S., Stability and control of piecewise-deterministic queueing systems,  arXiv preprint arXiv:1604.02008 (2016).

·      Jin, L. & Amin, S., A traffic model with switched dynamics for freeway incident management, arXiv preprint arXiv:1601.00204 (2016).

Journal Articles

·      Cao, Y., Jin, L., Nguyen, N. V. P., Landry, S., Sun, D., & Post, J. (2015) Evaluation of fuel benefits depending on continuous descent approach procedures, Air Traffic Control Quarterly, vol.22, no.3, pp.1-25.

·      Jin, L., Cao, Y., & Sun, D. (2013) Investigation of potential fuel savings due to continuous-descent approach, AIAA Journal of Aircraft, 50(3), 807-816.

Conference Proceedings

·      Jin, L. & Amin, S. (2017) Calibration of a macroscopic traffic flow model with stochastic saturation rates, Transportation Research Board 88th Annual Meeting, Washington, DC.

·      Jin, L. & Amin, S. (2014) A piecewise-deterministic Markov model of freeway accidents, Proceedings of the 53rd IEEE Conference on Decision and Control, Los Angeles, CA.


·      Jin, L. (2012) Design and evaluation of Continuous Descent Approach as a fuel-saving procedure, M.S. Thesis, Purdue University.


·      “Hierarchical control of freeway networks subject to disturbances,” System Science of SecUrity and Resilience for cyber-physical systems (SURE) Review Meeting in Arlington, VA, on November 18, 2015.

·      “A piecewise-deterministic Markov model of freeway accidents,” 53rd IEEE Conference on Decision and Control in Los Angeles, CA, on December 15, 2014.

·      “Stochastic hybrid modeling of flow network incidents,” Foundations of Resilient Cyber-Physical Systems (FORCES) All Hands Meeting in Oakland, CA, on June 16, 2014.



·      Discrete stochastic processes (6.262)

·      Dynamic programming and stochastic control (6.231)

·      Dynamic systems and control (6.241)

·      Optimization methods (6.255)

·      Applied probability (6.431)

·      Operations research in logistical and transportation planning (1.203)

·      Statistical learning and data mining (15.077)

·      Theory of probability (18.175)