PRX Intelligence

Anatole von Lilienfeld is the Ed Clark Chair of Advanced Materials, Full Professor at the departments of Chemistry, Materials Science & Engineering, and Physics at the University of Toronto, and a CIFAR AI Chair at the Vector Institute. He received his Ph.D. in computational chemistry from EPFL and is a leading figure in AI-accelerated discovery across chemistry and materials, integrating quantum mechanics, machine learning, and high-performance computing to explore chemical compound space and enable data-driven materials design. His recognitions include the Löwdin Lecture Award (Uppsala), the Foresight Institute’s Feynman Theory Prize, and a Woodward Lecture at Harvard University. As Chief Editor of PRX Intelligence, he will champion rigorous, high-impact research at the intersection of AI/ML and the physical sciences while fostering cross-disciplinary collaboration across domains.

Kyle obtained his Ph.D. in physics in 2016 at the University of Oregon, where he studied statistical physics in nonequilibrium fluid systems. He went on to work as a postdoctoral researcher studying the physics of active matter and microswimmers, jointly appointed in the Department of Chemical Engineering and Materials Science at the University of Minnesota and the Complex Systems Division at the Beijing Computational Science Research Center. He joined the PRL editorial team in 2019. In addition to his work in physics, Kyle also holds a B.S. in Neuroscience from Washington State University.

Ann Lee is a professor in the Department of Statistics & Data Science at Carnegie Mellon University (CMU), with a joint appointment in the Machine Learning Department. She received her Ph.D. in Physics at Brown University, and was the J.W. Gibbs Assistant professor in the department of mathematics at Yale University prior to joining CMU. Dr Lee’s expertise is in statistical and machine learning methodology for astronomy, fundamental physics, weather/climate and earth sciences. Her recent work includes neural simulation-based inference, calibrated predictive inference and probabilistic forecasting involving satellite imagery and large-scale studies. Dr Lee is the founder and co-director of the new STAMPS (Statistical Methods for the Physical Sciences) Research Center at Carnegie Mellon University. .

Nicola Marzari currently holds the Chair of Theory and Simulation of Materials at EPFL and heads the Laboratory for Materials Simulations at the Paul Scherrer Institut. He recently took up the post of Cavendish Professor of Physics at the University of Cambridge (UK), transitioning there in 2026. Previously, he held the Toyota Chair for Materials Processing at the Massachusetts Institute of Technology and was the inaugural Statutory Chair of Materials Modelling at the University of Oxford (UK). He received a Laurea in Physics from the University of Trieste and a Ph.D. in Physics from the University of Cambridge. His research is dedicated to the development and application of electronic-structure simulations and AI/ML methods to understand, predict, and design the properties and performance of novel materials and devices.

Ben is an associate professor of Particle Physics and Astrophysics and, by Courtesy, of Physics and Statistics at Stanford University and the SLAC National Laboratory. He received his Ph.D. (Minor) in Physics (Statistics) from Stanford University in 2016 after which he was a Chamberlain Fellow and then staff scientist at Lawrence Berkeley National Laboratory. His research focuses on developing, adapting, and deploying AI tools to facilitate discoveries in particle, nuclear, and astrophysics. He has received a number of awards for this research, including early career prizes from the American and European Physical Societies. Ben also serves on the executive board of the APS Group on Data Science.