
Encourages students to keep striving for excellence.
Encourages students to think independently.
Creates a positive and motivating atmosphere.
Encourages open-minded and thoughtful discussions.
Fosters collaboration and teamwork.
Dr. Fangyi Zhang is a Lecturer in the School of Electrical Engineering, Computing, and Mathematical Sciences in the Faculty of Science and Engineering at Curtin University, having joined in January 2025. He leads the Embodied Robotics & AI Lab (ERA Lab), dedicated to advancing robotics and artificial intelligence so that robots can acquire real-world skills through projects on tactile-based manipulation, compliant grasping with instrumented objects, deep learning for computer vision, sim-to-real transfer of visuo-motor policies, and applications in warehouse and household robotics. His research interests encompass robot learning, tactile sensing, robotic vision, robotic manipulation, and autonomous systems. Zhang earned his PhD in Robotics from the Australian Centre for Robotic Vision at Queensland University of Technology in 2018, with a thesis entitled “Learning Real-world Visuo-motor Policies from Simulation,” supervised by Professors Peter Corke, Jürgen Leitner, and Michael Milford. He holds a B.Eng. in Automation from East China Jiaotong University, awarded in 2010.
Prior to his current role, Zhang was a Research Fellow and Visiting Fellow at the QUT Centre for Robotics, an Algorithm Expert at Alibaba DAMO Academy developing drone applications, a Research Assistant at the Hong Kong University of Science and Technology working on VLC-based localization, and an R&D Engineer at CRRC Zhuzhou Institute focusing on locomotive control algorithms from 2010 to 2013. He has produced over 20 peer-reviewed publications in leading venues including The International Journal of Robotics Research (IJRR, 2019: “Adversarial discriminative sim-to-real transfer of visuo-motor policies”), IEEE Robotics and Automation Letters (RA-L, 2024: “Towards Assessing Compliant Robotic Grasping From First-Object Perspective via Instrumented Objects”), ICRA (2024, 2017), IROS (2023), NeurIPS (2022), and ICLR (2022). His work has accumulated over 1,000 citations on Google Scholar. Zhang has been honored with the Best Paper Award Finalist at ACRA 2017 and Best Industry Paper at IJCAIW 2021. At Curtin, he serves as Unit Coordinator for the postgraduate course CMPE6012 Artificial Intelligence and Machine Learning in Embedded Systems and organizes public lectures, such as an IEEE-EECMS event on visual SLAM in May 2025.
