Xinling Li

Ph.D in Transportation. JTL & LIDS

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Building 32, D640

32 Vassar St

Cambridge, MA 02139

I am a Ph.D at MIT in Transportation supervised by Prof.Jinhua Zhao and Prof.Gioele Zardini. I am affliated with the Urban mobility Lab (JTL) and the Laboratory for Information & Decision Systems (LIDS). My research focuses on the design and operation control of Autonmous Mobility-on-Demand (AMoD) service, as well as its interaction with the existing infrastructures.

Prior to MIT, I obtained my bachelor’s degree in Traffic Engineering from Tongji University in China, and my master’s degree in Mobility and Data Science from EPFL, Lausanne in Switzerland. During my masters’ year, I had the honor to exchange in the Machine Learning for Smart Mobility (MLSM) lab at DTU in Denmark, under the supervision of Prof.Filipe Rodrigues.

Check the webpage JTL and Zardini Lab for more information about our lab!

News

Aug 28, 2025 Our new paper on ‘Accelerating High-Capacity Ridepooling in Robo-Taxi Systems’ is available here :sparkles:
Jul 15, 2025 Our new paper on ‘Reproducibility in the Control of Autonomous Mobility-on-Demand Systems’ is available here :sparkles:
Jun 25, 2025 I presented our recent work on robo-taxi fleet coordination with high-capacity ridepooling in Robotis: Science and Systems (RSS) 2025 Workshop on Scalable and Resilient Multi‑Robot Systems. Checkout the workshop here! :palm_tree: :sunny:

Selected publications

  1. TR-C
    One-step gibbs sampling for the generation of synthetic households
    Marija Kukic, Xinling Li, and Michel Bierlaire
    Transportation Research Part C: Emerging Technologies, 2024
  2. T-ITS
    Learning Joint Rebalancing and Dynamic Pricing Policies for Autonomous Mobility-on-Demand
    Xinling Li, Carolin Schmidt, Daniele Gammelli, and 1 more author
    IEEE Transactions on Intelligent Transportation Systems, 2025
  3. arXiv
    Reproducibility in the Control of Autonomous Mobility-on-Demand Systems
    Xinling Li, Meshal Alharbi, Daniele Gammelli, and 7 more authors
    arXiv preprint arXiv:2506.07345, 2025