Speaker: Olexandr Isayev
Title: AIMNet2: Foundation neural network potential for molecules and reactions
Abstract: Deep learning is revolutionizing many areas of science and technology, particularly in natural language processing, speech recognition and computer vision. In this talk, we will provide an overview of the latest developments in machine learning and AI methods and application to the problem of drug discovery and molecular design at Isayev’s Lab at CMU. We identify several areas where existing methods have the potential to accelerate computational chemistry research and disrupt more traditional approaches.
Machine learned interatomic potentials (MLIPs) are reshaping computational chemistry practices because of their ability to drastically exceed the accuracy-length/time scale tradeoff. Despite this attraction, the benefits of such efficiency are only impactful when an MLIP uniquely enables insight into a target system or is broadly transferable outside of the training dataset, where models achieving the latter are seldom reported. In this work, we present the 2nd generation of our atoms-in-molecules neural network potential (AIMNet2), which is applicable to species composed of up to 14 chemical elements in both neutral and charged states, making it a valuable model for modeling the majority of non-metallic compounds.
Bio:
Date and Time: September 25, 2025, 11am-12pm CT / !2-1pm ET
Location: Coordinated Science Lab Auditorium (B02), 1308 W. Main St., Urbana IL 61801
This will be a wonderful opportunity to connect with other experts and engage in fruitful discussions.
https://go.illinois.edu/IIDAISeminar