Rate My Professor Chao Chen

Associate Professor Chao Chen serves in the Department of Mechanical and Aerospace Engineering within Monash University’s Faculty of Engineering. He joined the department as a Lecturer in 2007, was promoted to Senior Lecturer in 2011, and currently holds the position of Associate Professor. Since 2008, Chen has directed the Laboratory of Motion Generation and Analysis (LMGA), dedicated to advancing robotics and AI technologies to address challenges in agriculture, medicine, and infrastructure sectors. His academic background includes a PhD and a Master’s degree in Mechanical Engineering with a focus on robotics from McGill University, a postdoctoral fellowship at the University of Toronto from 2006 to 2007, and recognition on the Dean’s Honor List at Shanghai Jiao Tong University in 1996. Additional appointments include Senior Research Fellow at the University of Melbourne from 2015 to 2017, Adjunct Associate Professor at the Chinese University of Hong Kong, Visiting Professor at IRCCyN, Ecole Centrale de Nantes in 2011, and Visiting Professor at Shanghai Jiao Tong University in 2013. As primary chief investigator, he has attracted more than $2 million in research funding and participated in projects totaling $18 million from sources including the Australian Research Council and the Collier Charitable Fund.

Chen’s research specializations encompass agricultural robotics, medical robotics, infrastructural robotics, soft robotics, motion planning, and robotic intelligence. Under his leadership, the Monash Apple Retrieving System (MARS) earned the 2023 Excellence Award (Project of the Year) from Engineers Australia Victoria, and the 3D Printed Prosthetic Hand received the 2017 Year’s Innovation Award from the Australian Hand Therapy Association. His contributions align with UN Sustainable Development Goals 2 (Zero Hunger) and 3 (Good Health and Well-being). Key publications include “Intelligent robots for fruit harvesting: Recent developments and future challenges” (2022, Precision Agriculture), “Fast implementation of real-time fruit detection in apple orchards using deep learning” (2020, Computers and Electronics in Agriculture), “Development and evaluation of a robust soft robotic gripper for apple harvesting” (2023, Computers and Electronics in Agriculture), “Real-time fruit recognition and grasping estimation for robotic apple harvesting” (2020, Sensors), and “A hybrid statistical method to predict wind speed and wind power” (2010, Renewable Energy). Earlier honors include the 2004 ASME International Scholarship, 2005 FQRNT Doctorate Scholarship, and 2006-2007 FQRNT Post-Doctorate Fellowship.