Susan Wei is a lecturer (assistant professor) in the School of Mathematics and Statistics at the University of Melbourne. She previously held a Discovery Early Career Researcher Award (DECRA) and was a visiting faculty researcher at Google DeepMind in Sydney. Her research focuses on statistical machine learning, particularly in Bayesian approaches to deep learning, alongside variational inference and singular learning theory. She is part of the Melbourne Deep Learning Group and a founding organiser of GDG AI for Science - Australia.
PhD in Statistics, 2014
University of North Carolina, Chapel Hill
BA in Mathematics, 2009
University of California, Berkeley
In summer 2024, I co-organized a deep learning workshop in Lorne, Australia with Peter Bartlett. Here is the website of the workshop, which was generously supported by Google Research.
In Winter 2021, I gave a week-long lecture series on Neural Networks and Related Models as part of the Australian Mathematical Sciences Institute (AMSI) Winter School program, an annual event open to graduate students, early career researchers, and industry members across Australia. The course was an introduction to deep learning as well as some probabilistic models involving neural networks (flow-based models and deep generative models).
You can find my lecture slides here for Part 1 of the course where I covered the following topics:
The second part of the module on deep generative modeling was given by Robert Salomone. You can find his excellent teaching materials here.