Weiming (William) Zhi

Welcome to my homepage! 

I am a postdoctoral fellow with Prof. Matthew Johnson-Roberson at the Robotics Institute, Carnegie Mellon University.

Before CMU, I was PhD candidate at the School of Computer Science, the University of Sydney, Australia, supervised by Prof Fabio Ramos and working closely Dr Lionel Ott (now at ETH Zurich). My Doctoral thesis won the School's Outstanding Thesis Award. During my PhD, I spent time conducting robotics research with NVIDIA's Seattle Robotics Lab.

My research interests lie at the intersection of robotics and machine learning. My research focuses on the goal of developing robot systems that can learn from and about their environment, enabling them to safely operate in dynamic and unstructured environments.Under this general umbrella of robot learning, I have worked on a broad range of problems, which include learning probabilistic representations of occupancy and motion patterns, probabilistic motion trajectory prediction, anticipatory navigation under uncertainty, and leveraging invertible representations for generalised imitation learning and planning. Publications arising from these topics have found their way into top robotics venues, such as CoRL, IEEE RA-L, ICRA, IROS, L4DC. 

My research has led me to received international awards and recognitions, such as the L4DC 2022 Best Paper Award and Robotics: Science and Systems (RSS) Pioneer in 2020.

Before embarking on my PhD, I received my Bachelors of Engineering (Hon., first class) at the University of Auckland, New Zealand, specialising in engineering science and operations research.