Google DeepMind
work: [email protected]
personal: [email protected]
Oxford, UK
[Phone: +44 750 825 6803](tel:+44 750 825 6803)
2021-Presenthen : Staff Research Scientist at Google Brain (Google DeepMind from April 2023)
2021-2022 : Leverhulme Professor at the Department of Computer Science of the University of Oxford
2019-2021 : Visiting Researcher at Google (Staff Faculty Visiting Researcher)
2018-2019 : Visiting Researcher at the Department of Computer Science of the University of Oxford
2017 : Invited Professor at the École normale supérieure de Lyon (Laboratoire de l’Informatique du Parallélisme)
2016-2019 : Data Scientist at deepsense.ai, responsible for research projects related to machine learning
2007-Present : Lecturer and researcher at the Department of Mathematics, Informatics and Mechanics, University of Warsaw (on long-term leave; the last post held was Associate Professor)
2004-2007 : Postdoc at the Department of Mathematics of the Ben Gurion University, Israel. Working on topics related to logic and foundations of mathematics
I made individual contributions to code and reasoning trainings and evaluations of PaLM and Minerva models, and I am currently working on the next generation of code and reasoning models. I also work on the incorporation of new modalities for code, reasoning, and robotics that would allow self-improvement, error spotting and correction, and prediction of the value of a sequence of actions.
- RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control, RT-2 in New York Times, Google AI Blog, 2023.
- S. Tworkowski, K. Staniszewski, M. Pacek, Y. Wu, H. Michalewski, P. Miłoś Long Llama, GitHub repo - access to Long Llama using the HuggingFace API, 2023.
- A. Lewkowycz, A. Andreassen, D. Dohan, E. Dyer, H. Michalewski, V. Ramasesh, A. Slone, C. Anil, I. Schlag, T. Gutman-Solo, Y. Wu, B. Neyshabur, G. Gur-Ari, V. Misra: Solving Quantitative Reasoning Problems with Language Models | blog post | sample explorer - NeurIPS 2022.
- K.-H. Lee, O. Nachum, S. Yang, L. Lee, D. Freeman, W. Xu, S. Guadarrama, I. Fischer, E. Jang, H. Michalewski, I. Mordatch: Multi-Game Decision Transformers - NeurIPS 2022.
- PaLM: Scaling Language Modeling with Pathways - preprint 2022. Contribution to Section 6.4 on Code Generation with Large Language Models.
- S. Mouselinos, H. Michalewski, M. Malinowski: Measuring CLEVRness: Black-box Testing of Visual Reasoning Models - ICLR 2022.
- P. Yin, W.-D. Li, K. Xiao, A. Rao, Y. Wen, K. Shi, J. Howland, P. Bailey, M. Catasta, H. Michalewski, A. Polozov, C. Sutton: Natural Language to Code Generation in Interactive Data Science Notebooks - ACL 2023.
- S. Mouselinos, M. Malinowski, H. Michalewski: A Simple, Yet Effective Approach to Finding Biases in Code Generation - ACL 2023.
- P. Nawrot, S. Tworkowski, M. Tyrolski, Ł. Kaiser, Y. Wu, C. Szegedy, H. Michalewski: Hierarchical Transformers Are More Efficient Language Models - NAACL 2022.
- M. Nye, A. J. Andreassen, G. Gur-Ari, H. Michalewski, J. Austin, D. Bieber, D. Dohan, A. Lewkowycz, M. Bosma, D. Luan, C. Sutton, A. Odena: Show Your Work: Scratchpads for Intermediate Computation with Language Models - preprint 2021.
- J. Austin, A. Odena, M. Nye, M. Bosma, H. Michalewski, D. Dohan, E. Jiang, C. Cai, M. Terry, Q. Le, C. Sutton: Program Synthesis with Large Language Models - preprint 2021.
- L. Kaiser, M. Babaeizadeh, P. Milos, B. Osinski, R. H. Campbell, K. Czechowski, D. Erhan, C. Finn, P. Kozakowski, S. Levine, A. Mohiuddin, R. Sepassi, G. Tucker, H. Michalewski: Model-Based Reinforcement Learning for Atari - spotlight at ICRL 2020 (5% acceptance rate).
- S. Jaszczur, A. Chowdhery, A. Mohiuddin, L. Kaiser, W. Gajewski, J. Kanerva, H. Michalewski: Green Transformers: Sparse is Enough - NeurIPS 2021.
- P. Piekos, H. Michalewski, M. Malinowski: Measuring and Improving BERT’s Mathematical Abilities by Predicting the Order of Reasoning - ACL 2021.
- C. Kaliszyk, J. Urban, H. Michalewski, M. Olšák: Reinforcement learning of theorem proving - NeurIPS 2018.
- B. Osiński, A. Jakubowski, P. Zięcina, P. Miłoś, C. Galias, S. Homoceanu, H. Michalewski: Simulation-based reinforcement learning for real-world autonomous driving - ICRA 2020.
- S. Jaszczur, M. Łuszczyk, H. Michalewski: [Neural heuristics for SAT solving](https://rlgm.github.io/papers
2015 : habilitation in computer science, University of Warsaw. Thesis
Winter 2002 : Internship in the Fields Institute, Toronto, Canada
1998-2002 : PhD in Mathematics, University of Warsaw
1993-1998 : MA in Mathematics, University of Warsaw
- Spyridon Mouselinos, 2021-2025, Ph.D. project Towards visual reasoning, thesis co-supervised by Mateusz Malinowski (Google DeepMind).