Jack Valmadre

Senior Research Fellow
Australian Institute for Machine Learning
The University of Adelaide

I'm a researcher working on computer vision and deep learning. I'm passionate about using mathematics and programming to find elegant solutions to problems in machine learning. My research interests include optimisation, signal processing, structured prediction, weak supervision, zero- and few-shot learning, object tracking, open-world vision and long-tail learning.

Feel free to get in touch about research supervision; PhD or Masters!

Short bio: I obtained my PhD in 2016 from Queensland University of Technology under the supervision of Prof. Simon Lucey at CSIRO. After my PhD, I was a post-doc with Prof. Philip Torr at the University of Oxford, and then spent two and a half years at Google France, working with Prof. Cordelia Schmid. I studied Mechatronic Engineering at the University of Queensland and I used to build robots in high school.

News

2023-03: I was recognised as a Notable Reviewer at ICLR 2023.

2023-02: I served as Area Chair at CVPR for the first time.

2022-10: New paper accepted to NeurIPS 2022! “Hierarchical classification at multiple operating points”

2022-02: I've joined AIML at the University of Adelaide!

2021-09: Our open-source Python package for evaluating local multi-object tracking metrics, localmot, is now on Github.

2021-08: I was recognised as an outstanding reviewer for ICCV 2021! (top 5% of experienced reviewers)

2021-04: Our article “Local metrics for multi-object tracking” is now on arXiv.