Ye Pu (蒲晔)
Senior Lecturer (Assistant Professor), ARC Discovery Early Career Researcher Award Fellow 2022-2025
Department of Electrical and Electronic Engineering
The University of Melbourne.
Contact:
Office: Room 3.06, Electrical and Electronic Engineering Building
Email: ye.pu@unimelb.edu.au
Short biography:
Ye received the B.S. degree from Shanghai Jiao Tong University, China, in 2008, the M.S. degree from the Technical University Berlin, Germany, in 2011, and the PhD degree from the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, advised by Prof. Colin Jones and Prof. Melanie Zeilinger from ETH in 2016. From 2016 to 2018, she was a postdoctoral researcher advised by Prof. Claire Tomlin at the University of California at Berkeley, USA.
Ye received the Swiss National Science Foundation, Early Postdoc.Mobility fellowship in 2016-2018. She is a recipient of the ARC Discovery Early Career Researcher Award in 2022-2025.
Research Interests:
Optimisation-based control (model predictive control and reachability analysis),
Optimisation algorithms
Multi-agent dynamical systems
Learning-based control
Underwater robotics
Ph.D. students:
Seth Siriya (on safe control and learning, co-supervised with Prof Dragan Nesic and Dr Jingge Zhu)
Yujia Yang (on real-time model predictive control, co-supervised with Prof Chris Manzie)
Jinghe Yang (on vision-based perception and control for underwater robots, co-supervised with Dr Mingming Gong and Prof Girish Nair)
Lei Qin (on efficient distributed optimisation for non-convex problems, co-supervised with Prof Michael Cantoni)
Nour Wahba (as co-supervisor, on learning-based control for building systems, co-supervised with Behzad Rismanchi and Prof Aye Lu)
Mingliang Liu (as co-supervisor, on multi-agent system control, co-supervised with Prof Ying Tan)
Teaching:
ELEN90054 Probability and Random Models in SM2, 2019-2020.
ELEN90056 Introduction to Optimisation in SM2, 2021-present.
Selected Capstone projects (master thesis projects)
“Optimal Path Planning and Following for Race Cars" in 2019. The project won the EEE Merit Award.
”Optimal Path-Planning/Following for Autonomous Vehicles using Partial Information" in 2020. The project won the People's Choice Runner-Up Prize and Road to Endeavour Runner-Up Prize.
"Vision-Based Autonomous Underwater Vehicle Platform Development" in 2021. The project won the EEE Merit Award and an industrial award - the IMarEST Endeavour Award.
"Learning-based Model Predictive Control for Unmanned Surface Vehicles based on Cameras" in 2022. The project won the EEE Merit Award.