Yanran Wang is a Ph.D. student at Imperial College London, where he is fortunate to be supervised by Dr. David Boyle and co-supervised by Prof. Robert Shorten. Prior to joining Imperial College, he received an M.S. degree in Information and Control at Shanghai Jiao Tong University, Shanghai, China, in 2020, and a B.S. degree in Automation at Southeast University, Nanjing, China, in 2017.

His research interest lies in Trustworthy Autonomous System Design, with a focus on achieving Interpretability via Formal Guarantees in reinforcement learning and optimal control theories. Particularly, he is keen on applying these theories to intelligent aerial robots to practically verify the decision-interpretation. Please feel free to reach out should you be interested in his research.

Beyond his academic pursuits, he has a deep passion for classical music and sports.

Academic Services

I was invited to serve as a reviewer for several prominent conferences in the machine learning and robotics community during the recent 2023-2024, including ICLR, CoRL, ICRA, IROS, and CDC. I also served as a reviewer for esteemed journals such as IEEE Robotics and Automation Letters (RA-L), IEEE Transactions on Automation Science and Engineering (IEEE T-ASE), the International Journal of Robust and Nonlinear Control, and Aircraft Engineering and Aerospace Technology.

Reminder [Calendar]

News

• August 2024, I gave an invited online seminar at MIT, hosted by Prof. Gioele Zardini.
• June 2024, our paper “Constrained Reinforcement Learning using Distributional Representation for Trustworthy Quadrotor UAV Tracking Control” was accepted to the IEEE Transactions on Automation Science and Engineering (IEEE T-ASE) !
• May 2024, our paper “Probabilistic Constrained Reinforcement Learning with Formal Interpretability” was accepted to the 41st International Conference on Machine Learning (ICML). Will see you in Vienna, Austria, on July 21st-27th.
• May 2024, our paper “On solving close enough orienteering problems with overlapped neighborhoods” was accepted to the European Journal of Operational Research (EJOR).
• November 2023, I gave an invited talk at Shanghai Jiao Tong University, hosted by Prof. Gang Xiao.
• May 2023, I gave an invited talk in the Autonomous Robotics and Control Lab at Caltech, hosted by Prof. Soon-Jo Chung.
• January 2023, I gave an invited talk in REDS Lab at Imperial College London, hosted by Prof. Nicolas Rojas and Kelin Li.
• September 2022, our paper “QuaDUE-CCM: Interpretable Distributional Reinforcement Learning using Uncertain Contraction Metrics for Precise Quadrotor Trajectory Tracking” was accepted to the 6th Conference on Robot Learning (CoRL), in Auckland, New Zealand, 2022.
• July 2022, our paper “Interpretable Stochastic Model Predictive Control using Distributional Reinforced Estimation for Quadrotor Tracking Systems” was accepted to the 62nd IEEE Conference on Decision and Control (CDC). I will give a talk on December 5th, in Cancún, Mexico.
• May 2022, I will give an oral presentation on ICRA 2022 in person, in Philadelphia. Hopefully see you all!
• January 2022, our paper “KinoJGM: A framework for efficient and accurate quadrotor trajectory generation and tracking in dynamic environments” was accepted to the 39th IEEE International Conference on Robotics and Automation (ICRA) in Philadelphia, United States!
• November 2021, I just passed my Early Stage Assessment (ESA) :)
• May 1st, 2021, I am very excited to enroll in Dyson School at Imperial College as a PhD candidate!
• April 1st, 2020, I will be a PhD student at Imperial College London.
• March 31st, 2020, I graduate with a master’s degree (with honor) from Shanghai Jiao Tong University.

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