Accelerating Quantum Materials Discovery Workshop

June 22-25, 2026

Colorado School of Mines

Overview: This workshop brings together researchers in quantum materials and artificial intelligence with the shared goal of accelerating discovery by tightly coupling data, theory, and experiment. We will cover the full discovery loop — materials synthesis (bulk powders, thin films, and single-crystal growth), characterization and analysis, and computational approaches that both guide synthesis decisions and help interpret complex experimental results. On the AI side, topics will span symmetry-aware and physics-informed representations, generative models for proposing candidate materials and experiments, and practical human–machine interaction patterns that make these tools usable at the bench. A central theme is building a common technical language: grounding AI methods in the constraints and objectives of real materials workflows, while framing quantum materials problems in a way that is accessible to non-specialists.

Structure: The workshop will be a combination of invited talks, poster sessions, and workshop breakout groups.

Participants: The workshop is open to participants at all levels (faculty, postdocs, graduate students).

Financial support: This workshop is supported by the NSF Institute for Data Driven Dynamical Design (ID4). There is no registration fee, and we anticipate being able to cover the majority of participant travel costs using NSF funding.

If you have been invited, register for the workshop here: https://forms.gle/oi5nHQjYsNESDJWL8

Organizing Committee

Jason Khoury, Arizona State University
Aditi S Krishnapriyan, University of California, Berkeley
Grace Pan, University of Michigan
Brenden Ortiz, Oak Ridge National Laboratory
Eric Toberer, Colorado School of Mines
Thao Tran Dominy, Clemson University