
University of Melbourne
Brings passion and energy to teaching.
Encourages innovative and creative solutions.
Always positive and enthusiastic in class.
Always approachable and easy to talk to.
Great Professor!
Professor Tom Drummond is the Melbourne Connect Chair of Digital Innovation for Society in the School of Computing and Information Systems, Faculty of Engineering and Information Technology, at the University of Melbourne. He obtained a BA in Mathematics from the University of Cambridge between 1985 and 1988, and a PhD from Curtin University between 1994 and 1998, with a thesis titled 'Learning to recognise important objects in a visual environment'. Early in his career, he served as Director of Cambridge Video Unit Ltd and Cambridge Cooperative Development Agency Ltd from 1988 to 1989, and as Assistant to the Communications Manager at CSIRO Division of Mineral and Process Engineering from 1990 to 1994. From 1998 to 2001, he was a Research Associate at the University of Cambridge, followed by University Lecturer from 2001 to 2004 and University Senior Lecturer from 2005 to 2010. He then joined Monash University as Professor from 2010 to 2021, serving as Head of the Department of Electrical and Computer Systems Engineering from 2016 to 2017 and 2018 to 2021, and as Chief Investigator and Monash Node Leader for the ARC Centre of Excellence in Robotic Vision. Since July 2021, he has held his current chair position at the University of Melbourne.
Drummond's academic interests center on Artificial Intelligence, Machine Learning, High Performance Computing, and Computer Vision, with a focus on real-time systems for Augmented Reality, Robotics, and Assistive Technologies. His primary research interest is Computer Vision. He has been awarded the Könderink prize and the ISMAR 10-year impact award, and has secured ARC and EU Framework research grants totaling over $35 million AUD, in addition to funded industry collaborations. He was a member of the Victorian Road Safety Commissioner Reference Group. Key publications include 'Scalable Monocular SLAM' (Eade and Drummond, 2006), 'Edge Landmarks in Monocular SLAM' (Eade and Drummond, 2006), 'Faster and Better: A Machine Learning Approach to Corner Detection' (Rosten, Porter, and Drummond, 2006), 'Real-Time Visual Tracking of Complex Structures' (Drummond and Cipolla, 2002), and 'Learning Instance and Task-Aware Dynamic Kernels for Few-Shot Learning' (2022). His work has accumulated over 24,000 citations according to Google Scholar.
Professional Email: tom.drummond@unimelb.edu.au