Matthew T. Jackson

DPhil student at the University of Oxford


I’m a third year DPhil student at the University of Oxford, where I am co-supervised by Jakob Foerster and Shimon Whiteson. I’m also a member of the AIMS CDT.

I’ll be starting a research internship at Wayve in May 2024, working in the World Models Team on the next generation of GAIA.

I’ve completed software engineering internships at Amazon, Arm and Cubica (since acquired), working on natural language processing, computer vision and efficient network inference. I previously completed an MSc in Machine Learning from University College London and a BA in Computer Science from the University of Cambridge.


I’m interested in making agents learn faster than humans. Two promising approaches to this are learning from synthetic data and learning generalizable policies and algorithms with meta-reinforcement learning.

Policy-Guided Diffusion

Matthew T. Jackson, Michael T. Matthews, Cong Lu, Benjamin Ellis, Jakob Foerster, Shimon Whiteson

Under review - NeurIPS 2023 Workshop on Robot Learning   paper

Discovering Temporally-Aware Reinforcement Learning Algorithms

Matthew T. Jackson*, Chris Lu*, Louis Kirsch, Robert T. Lange, Shimon Whiteson, Jakob N. Foerster

International Conference on Learning Representations (ICLR) 2024   paper

Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design

Matthew T. Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster

Neural Information Processing Systems (NeurIPS) 2023   paper

Further Publications

Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning

Michael Matthews, Michael Beukman, Benjamin Ellis, Mikayel Samvelyan, Matthew T. Jackson, Samuel Coward, Jakob Foerster

International Conference on Machine Learning (ICML) 2024   paper

Near to Mid-term Risks and Opportunities of Open Source Generative AI

Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schroeder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew T. Jackson, Paul Röttger, Philip H.S. Torr, Trevor Darrell, Yong Suk Lee, Jakob Foerster

International Conference on Machine Learning (ICML) 2024   paper

SplAgger: Split Aggregation for Meta-Reinforcement Learning

Jacob Beck, Matthew T. Jackson, Risto Vuorio, Zheng Xiong, Shimon Whiteson

Under review   paper

Retrieve What You Need: A Mutual Learning Framework for Open-domain Question Answering

Dingmin Wang, Qiuyuan Huang, Matthew T. Jackson, Jianfeng Gao

Transactions of the Association for Computational Linguistics (TACL) 2024   paper

Online Reinforcement Learning Controllers for Soft Robots using Learned Environments

Uljad Berdica, Matthew T. Jackson, Jakob Foerster, Perla Maiolino

International Conference on Soft Robotics (RoboSoft) 2024

Hypernetworks in Meta-Reinforcement Learning

Jake Beck, Matthew T. Jackson, Risto Vuorio, Shimon Whiteson

Conference on Robot Learning (CoRL) 2022   paper

Multi-Modal Fusion by Meta-Initialization

Matthew T. Jackson*, Shreshth A. Malik*, Michael T. Matthews, Yousuf Mohamed-Ahmed

FARSCOPE Robotics Workshop 2022; Best Poster Award   paper