Mingda Xu is a postdoc at CVLab, EPFL working with Prof. Pascal Fua. I completed my bachelor's degree at the University of Melbourne in Actuarial Studies. After a brief stint in industry as an actuarial analyst, he completed a master's in mathematics at the University of New South Wales, followed by a PhD in robotics at the Queensland University of Technology, where he conducted research on visual localisation and mapping for mobile robots. His PhD thesis titled "Bridging the Divide between Visual Place Recognition and SLAM" was awarded the Faculty of Engineering Executive Dean’s Commendation for Outstanding Doctoral Thesis. Prior to his current appointment at EPFL, he was a research fellow at the Australian National University.

Mingda has broad research interests across robotics, computer vision, machine learning, automatic control and computational Bayesian statistics. His recent works revolve around numerical optimisation, optimal control, co-design of shape and control and unsupervised learning in computer vision. He was a finalist for the best paper award at CVPR 2024 and furthermore, he regularly reviews for conferences and journals such as ICRA, IROS, RSS, IJRR, NeurIPS, ICLR, ICML, ICCV, CVPR, ECCV,  IJCV and PAMI. Please see the linked Google Scholar profile for specific publications.