As Principal Scientist and Head of AI Research at the Ellison Institute of Technology (EIT), I am committed to advancing AI-driven breakthroughs that accelerate scientific discovery and real-world impact. With over 13 years of experience at the intersection of machine learning, generative models, and AI for the sciences, my work has spanned medicine, materials science, computational physics, and beyond.
Previously, as Director at Google DeepMind, I led high-impact research teams tackling some of AI’s most complex challenges—from variational inference and normalizing flows to AI for nuclear physics, medical imaging, genetics, and embodied agents. My contributions include 110+ papers and patents, shaping the field of AI and its applications in scientific discovery.
At EIT, I am excited to build and lead world-class AI teams that bring together AI, mathematics, physics, and biology to tackle pressing global challenges. Whether it’s developing foundation models for materials discovery, drug design, patient journeys, clinical trials, or experimental design, my goal is to push the boundaries of what AI can achieve in scientific research, healthcare, and sustainability.
I hold a Ph.D. in Computational Neuroscience from École Polytechnique Fédérale de Lausanne (EPFL), an MSc in Theoretical Physics from École Polytechnique (France) and the Institute of Theoretical Physics (Brazil), and a BSc in Physics from École Polytechnique.
All opinions expressed in this domain are my own.
Thank you for the notes, great stuff!
Thank you for sharing.
I have checked your papers and I haven’t seen one about GANs. I wonder if there is a special reason for this. Because I have been trying to learn GANs for my studies.