Most problems in chemical engineering require understanding kinetic, thermodynamics, and transport processes at atomistic scales. In many cases we may even understand the underlying physics and quantum chemistry, but the simulations are too expensive to tackle quickly the engineering design problems we want to solve.
Zack Ulissi
Meta FAIR
I will discuss why a fundamental AI/ML research team at Meta is so excited about chemistry and materials, introduce six open science simulation datasets we’ve released that are each among the largest in the world (spanning catalysts, inorganic materials, molecular crystals, and molecules/electrolytes), and then discuss our progress so far towards open science AI/ML models that span all of these areas (the Universal Model for Atoms, UMA). I will also show some preliminary results from our team and the rest of the community tackling problems in energy, healthcare, and beyond.
Zack Ulissi is a senior research scientist manager on the FAIR Chemistry team in Meta’s Fundamental AI Research lab and an Adjunct Professor of Chemical Engineering at Carnegie Mellon University. Prior to Meta, he was an Associate Professor of Chemical Engineering at CMU. He completed his undergraduate work at the University of Delaware, M.A.St. at Cambridge University, Ph.D. at MIT on carbon nanotube devices with Michael Strano and Richard Braatz, and post-doc in catalysis at Stanford with Jens Nørskov.
The CBEGSO hosts a reception with light refreshments prior to all the seminars in the Hesburgh Library Scholars Lounge at 10:15 am.