Events Calendar

Upcoming workshops, seminars, and convenings from AI-MI, bringing together researchers and partners to explore advances at the intersection of AI and materials science.

Upcoming Events

AI-MI Seminar Series: Sharon Li, Thursday, November 12, 2026

AI-MI Seminar Series: Sharon Li (University of Wisconsin-Madison)

Reliability Along the Way: Progress and Failure Signals in AI Agents — AI systems are rapidly evolving from models that generate responses to agents that execute long-horizon workflows, interact with tools and environments, and take increasingly consequential actions. This shift changes the nature of the reliability problem.

AI-MI Fest

Cornell Tech

Community

A day of bold ideas, sharp debate and new collaborations at the frontier of AI and materials science, at Cornell Tech in New York City.

Events Archive

AI-MI Seminar Series: Adrian Del Maestro (University of Tennessee, Knoxville)

AI-MI Seminar Series: Adrian Del Maestro (University of Tennessee)

Seminar

Predictions for helium on atomically thin substrates depend sensitively on the adsorption potential. Adrian Del Maestro (University of Tennessee, Knoxville) combines coupled-cluster calculations, multi-fidelity Gaussian process regression and knowledge distillation to reach single-wavenumber accuracy.

AI-MI Seminar Series: Daniel Tabor (Texas A&M University)

AI-MI Seminar Series: Daniel Tabor (Texas A&M University)

Seminar

Machine Learning Methods for Molecular Design and Reaction Discovery — This talk will discuss strategies we have developed for efficiently navigating chemical space, and the physical insights we gained during their design and deployment. The first part will focus on our work in developing methods that accelerate the prediction of properties of molecules and materials at multiple length scales.
AI-MI Seminar Series: Heng Ji (University of Illinois Urbana-Champaign)

AI-MI Seminar Series: Heng Ji (University of Illinois Urbana-Champaign & NSF MMLI)

Seminar

Agentic Modular Chemical Language Model (mCLM-A) for Molecule Discovery — Heng Ji introduces Science-Inspired Agentic AI, a paradigm that reimagines large language models as executable scientific agents rather than conversational assistants, with applications in drug and materials discovery.

AI-MI Seminar Series: Nima LeClerc (Diraq)

Seminar

Quantum devices are hard to calibrate and control at scale. Nima LeClerc (Diraq) presents a unified digital twin framework for designing and controlling quantum hardware, pairing GPU-accelerated simulation with meta-reinforcement learning — and scaling laws for when adaptation pays for itself.

Notable Past Events