Yanran Ding

Yanran Ding is an Assistant Professor in the Department of Robotics at the University of Michigan, directing the Agile Robot Control and Design (ARCaD) Lab. His research focuses on optimization-based control, actuator design, and trajectory planning for legged robots, aiming to bridge theoretical foundations with practical hardware implementations. He holds a Ph.D. from the University of Illinois at Urbana-Champaign and a B.S. from Shanghai Jiao Tong University. Prior to U-M, he was a Postdoctoral Associate at MIT’s Biomimetic Robotics Lab.

Education:

• Ph.D., Mechanical Engineering, University of Illinois Urbana-Champaign (2017–2021)
• M.S., Mechanical Engineering, University of Illinois Urbana-Champaign (2015–2017)
• B.S. (with Honors), Joint Institute, Shanghai Jiao Tong University (2011–2015)

Research interests emphasize optimization-based control algorithms, actuator design, and reinforcement learning applied to legged robots. His work enables agile motions through mechatronics integration and real-time model predictive control (MPC). Recent projects include energy-efficient legged locomotion and humanoid robot actuator design funded by a $1.2M grant.

Publications span topics like MPC for dynamic walking, self-collision avoidance, and open-source robotics kits. Notable trends include advancing MPC techniques for real-world robot agility and integrating hardware-software co-design principles.

Awards include the 2021 Best Paper Finalist Award (Model-Based Optimization TC), 2019 Coordinated Science Lab Best Robotics Demo Award, and multiple scholarships for academic excellence.

ARCaD Lab is actively hiring post-doctoral researchers. Current research includes robotic jumping, terrain-adaptive locomotion, and collaborative robotics systems. Lab activities include public demonstrations (e.g., robot dog Go2 at Ann Arbor Museum) and international conference presentations (ICRA, Humanoids).