About me
I am co-founder and CEO of a stealth startup. Previously, I was a research scientist at Google DeepMind. I was awarded the
MIT Innovators Under 35 award in 2023 for my work on discovering new algorithms with machine learning. I obtained my PhD from the signal processing laboratory in EPFL in 2016.
Research interests: I work on AI for Science, and in particular on using Machine Learning to unlock new results in Mathematics and Computer Science. I am also broadly interested in the reliability of Machine Learning systems, and in particular in computer vision.
Selected publications
Mathematical discoveries from program search with large language models Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Matej Balog, M. Pawan Kumar, Emilien Dupont, Francisco J. R. Ruiz, Jordan S. Ellenberg, Pengming Wang, Omar Fawzi, Pushmeet Kohli, Alhussein Fawzi
Nature 2023
Blog post
Press:
The Guardian,
New Scientist,
MIT Technology Review,
Nature News
Discovering faster matrix multiplication algorithms with reinforcement learning Alhussein Fawzi, Matej Balog, Aja Huang, Thomas Hubert, Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Francisco J. R. Ruiz, Julian Schrittwieser, Grzegorz Swirszcz, David Silver, Demis Hassabis, Pushmeet Kohli
Nature 2022 [Cover]
Blog post
Nature research briefing
Press:
MIT Technology Review,
New Scientist,
The Independent,
Venture Beat,
Nature
Learning dynamic polynomial proofs
Alhussein Fawzi, Mateusz Malinowski, Hamza Fawzi, Omar Fawzi
Neural Information Processing Systems (NeurIPS) 2019 [Spotlight presentation]
Software
Universal adversarial perturbations
Implementation of the algorithm for computing universal perturbations
GitHub page
DeepFool
Implementation of the DeepFool algorithm for fooling deep neural networks
GitHub page
Learning Algorithm for Soft-Thresholding (LAST)
Implementation of the DC-based dictionary learning algorithm for soft-thresholding based based classifiers.
Download MATLAB code.