Dr. Fangyi Zhang is currently a research fellow in the QUT Centre for Robotics. He was also a former PhD student in the Australian Centre for Robotic Vision (ACRV) at QUT node, supervised by Prof. Peter Corke, Dr. Jürgen Leitner, Prof. Michael Milford and Dr. Ben Upcroft. His PhD research was focused on Deep Reinforcement Learning and Transfer Learning for Robotic Reaching, and obtained the degree in 2018 with the thesis entitled “Learning Real-world Visuo-motor Policies from Simulation”. After that, he joined Alibaba DAMO Academy as a Research Scientist, doing research and development work on drone applications and data mining. His current research interests include robot learning, robotic vision, robotic manipulation, and autonomous systems.
Prior to his PhD, Fangyi obtained his B.Eng. degree in Automation from the East China Jiaotong University in 2010, followed with three years' work experience on R&D of locomotive control algorithms and electrical systems in the CRRC Zhuzhou Institute from 2010 to 2013. In 2014, he stayed for one year at the Hong Kong University of Science and Technology, as a research assistant supervised by Prof. Ming Liu, doing research on VLC-based indoor localization and 2D-laser based 3D sensing.
Ph.D. in Robotics and Artificial Intelligence, 2018
Australian Centre for Robotic Vision (ACRV), Queensland University of Technology (QUT)
B.Eng. in Automation, 2010
East China Jiaotong University (ECJTU)
This is my Ph.D. project in the Australian Centre for Robotic Vision at QUT, with supervisions from Prof. Peter Corke, Dr. Jürgen Leitner, Prof. Michael Milford and Dr. Ben Upcroft.
Amazon Picking Challenge (2016) As part of the Team ACRV for the Amazon Picking Challenge 2016, I worked on hand-eye calibration with Dr. Leo Wu. Household Applications This is a project I worked on during my visit to the Perception and Robotics Group at the University of Maryland, College Park, Sep-Dec 2016.
This is a project I worked on with Prof. Ming Liu and Mr. Kejie Qiu when I was a research assistant in the RAM-LAB at HKUST. Contributions: Developed a beacon code selection algorithm and a decomposition algorithm for blindly mixed beacon signals, based on CDMA code selection principles and Gold-sequence correlation properties.