[ About | Vision | Papers | Talks | Social | Blog | Personal ]
I'm a PhD student on the AIMS CDT supervised by Professor Mark van der Wilk in the Department of Computer Science at the University of Oxford.
Training modern AI systems is absurdly resource intensive, requiring huge datasets and expensive data centres. In contrast, we as humans can learn much more efficiently, in terms of data and memory consumption. How can we develop AI algorithms that can learn as efficiently and robustly as humans can learn? Answering this question is the goal of my research.
| 2026 |
"On The Scalability Of Forward Gradients, Evolution Strategies, And Control Variates" | Jake Levi, Seth Nabarro, Mark van der Wilk | Transactions on Machine Learning Research (TMLR) [ pdf | openreview | tweet ] |
| 2025 |
"SynDaCaTE: A Synthetic Dataset For Evaluating Part-Whole Hierarchical Inference" | Jake Levi, Mark van der Wilk | Methods and Opportunities at Small Scale (MOSS) workshop, ICML 2025 [ abstract | pdf | poster | tweet ] |
| 2024 |
"Welfare Equilibra As A Solution To Stackelberg Self-Play In Non-Coincidental Games" | Jake Levi, Chris Lu, Timon Willi, Christian Schroeder de Witt, Jakob Foerster | Pre-print [ abstract | pdf ] |
Besides rock climbing (trad + sport + bouldering), cinema, and playing classical guitar, my major passion is designing HTML websites. If you would like me to design your website, email me at
<a href="mailto:example@email.com">ERROR! BROKEN LINK</a>.