Anjian Li

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Hi! I am a 5th year PhD candidate in the Department of Electrical and Computer Engineering at Princeton University, advised by Prof. Ryne Beeson. I also work closely with Prof. Adji Bousso Dieng and Prof. Bartolomeo Stellato. My research focuses on generative AI and world models for safe, reliable reasoning and decision-making in complex environments, with applications to autonomous systems and robotics. I’m also interested in developing machine learning methods to accelerate non-convex optimization.

Over the past summer, I interned with Waymo planning team, where I worked on post-training a generative foundation model that is currently running on thousands of fully autonomous vehicles.

Previously I did an internship at Honda Research Institute USA, working on consistency models. I did my master in computing science at Simon Fraser University, advised by Prof. Mo Chen. Before that, I received my bachelor in mathematcis at Beijing Normal University.

news

Jun 02, 2025 I started a summer internship at Waymo!
Feb 28, 2025 Our paper DiffuSolve: Diffusion-Based Solver for Non-Convex Trajectory Optimization has been accepted to 7th Annual Learning for Dynamics & Control Conference (L4DC)!
Aug 23, 2024 I finished my internship at Honda Research Institute USA! It has been a wonderful experience working with Faizan M. Tariq, Sangjae Bae and David Isele in the team.

selected publications

  1. li2025end.png
    Predictive Planner for Autonomous Driving with Consistency Models
    Anjian Li, Sangjae Bae, David Isele, Ryne Beeson, and Faizan M. Tariq
    arXiv, 2025
  2. li2025diffusolve.png
    DiffuSolve: Diffusion-Based Solver for Non-Convex Trajectory Optimization
    Anjian Li, Zihan Ding, Adji Bousso Dieng, and Ryne Beeson
    7th Annual Learning for Dynamics & Control Conference (L4DC), 2025
  3. zhang2024predicting.png
    Predicting Long-Term Human Behaviors in Discrete Representations via Physics-Guided Diffusion
    Zhitian Zhang, Anjian Li, Angelica Lim, and Mo Chen
    In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024
  4. li2021prediction.png
    Prediction-based Reachability for Collision Avoidance in Autonomous Driving
    Anjian Li, Liting Sun, Wei Zhan, Masayoshi Tomizuka, and Mo Chen
    In IEEE International Conference on Robotics and Automation (ICRA), 2021
  5. li2020generating.png
    Generating Robust Supervision for Learning-Based Visual Navigation using Hamilton-Jacobi Reachability
    Anjian Li, Somil Bansal, Georgios Giovanis, Varun Tolani, Claire Tomlin, and Mo Chen
    In Learning for Dynamics and Control (L4DC), 2020