Artificial Intelligence Materials Institute (AI-MI)

Artificial Intelligence Materials Institute (AI-MI) is sponsored by National Science Foundation (NSF). A collaboration between six top research universities to accelerate the discovery of next-generation materials essential for energy, sustainability, and quantum technologies through AI integration.

The Artificial Intelligence Materials Institute @ Cornell University Watch our AI-MI Seminar Series talks, live on YouTube ! Accelerating next-generation materials research with AI. The AI-MI interdisciplinary team works on the interface of AI and materials research.

Led by Cornell University, NSF AI-MI is accelerating the discovery of next-generation materials essential for energy, sustainability and quantum technologies. By bringing together computer scientists, materials researchers and data scientists, AI-M tackles knowledge- and data-centric challenges to advance AI and materials science.

The institute integrates data generation, AI analysis and rapid experimental feedback to dramatically reduce the time it takes to discover new materials – from months to days – and to establish reproducible, reusable workflows for the broader research community. Funded by NSF with additional support from Intel Corporation.

The Artificial Intelligence Materials Institute is a collaboration between Boston University College of Engineering The City College of New York ASRC at the CUNY Graduate Center Massachusetts Institute of Technology Boston University College of Engineering The City College of New York ASRC at the CUNY Graduate Center Massachusetts Institute of Technology “Materials move and change the world.

Now, for the first time, we’re on the verge of designing matter with intention —turning data and algorithms into the architects of new materials. ” — Eun-Ah Kim, Lead PI, Cornell University Dr. Eun-Ah Kim is the founder and lead PI of AI-MI @ Cornell University AI-MI Director Eun-Ah Kim gave a talk at the Kavli Institute for Theoretical Physics program AI for Quantum Matter, where she also serves as a scientific advisor.

Fourteen undergraduate researchers completed the AI-MI Summer Undergraduate Research Program (SURP) on Friday, August 7, closing ten weeks at Cornell with final project presentations across both program tracks. AI-MI welcomes Jacob Gardner of the University of Pennsylvania, who joins the institute as senior personnel.

Gardner is an expert in probabilistic machine learning and Bayesian optimization, applying generative modeling to scientific discovery —… Two AI-MI researchers were on the program at M2S 2026 , the flagship international conference on the materials and mechanisms of superconductivity, held in Stuttgart July 19–25.

AI-MI Director Eun-Ah Kim (Cornell University) gave an invited talk,… AI-MI researchers continued to make their mark at the International Conference on Machine Learning (ICML 2026) in Seoul.

Kilian Weinberger, serving as ICML 2016 program co-chair, led the selection process for this year’s Test of Time Award; his… A machine-learning-guided search has identified two new kagome superconductors — YRu₃B₂ and LuRu₃B₂ — in a discovery covered widely by science media including SciTechDaily, ScienceDaily, Interesting Engineering, and TechTimes.

The work, led by the SuperC consortium (Rice/Aalto), was published in Physical Review Research (June 2026) and uses ML pre-screening followed by targeted quantum calculations and laboratory synthesis. AI-MI faculty members Emilia Morosan (Rice) and B. Andrei Bernevig (Princeton) are co-authors of the underlying paper.

Note: this paper does not acknowledge the AI-MI grant; it is featured here as member press. Kagome lattice superconductor structure. Image: SciTechDaily.

Source: SciTechDaily AI-MI senior personnel Emilia Morosan, Trustee Professor of Physics and Astronomy at Rice University and director of the Rice Center for Quantum Materials, has been named founding director of Q-RaMP — a new joint program between Rice University and the Max Planck Society to advance global leadership in quantum materials research and technology.

The partnership launched July 2, 2026, and is confirmed by both Rice News and a Max Planck Society press release. Morosan’s work in quantum materials and materials discovery is central to AI-MI’s mission. Source: Rice News AI-MI was well-represented at the International Conference on Machine Learning (ICML 2026, Seoul, July 11–19).

Eun-Ah Kim, AI-MI Director, co-organized the “AI for Physics” workshop and moderated its opening panel, “AI4Physics and the Current AI Revolution. ” John Thickstun (Cornell CS, AI-MI senior personnel) presented a poster on “Scaling Beyond Masked Diffusion Language Models,” demonstrating that uniform-state and interpolating discrete diffusion language models can be made ~12% more FLOPs-efficient.

Yoav Artzi (Cornell CS, AI-MI senior personnel) served on the ICML 2026 Outstanding Paper selection committee. Source: ICML 2026 AI-MI faculty member Emilia Morosan — Director of the Rice Center for Quantum Materials and Trustee Professor of Physics and Astronomy at Rice University — organized and keynoted the 2026 RCQM–KAST InterAcademy Global Workshop on Quantum Materials Synthesis, held June 9–12 at the Rice Global Paris Center.

The four-day workshop convened leading physicists, chemists, and materials scientists from around the world to tackle the synthesis challenges at the heart of quantum materials discovery. Delivering the opening and closing remarks, Morosan emphasized that “quantum materials are the foundation” for advancing quantum technologies.

Source: Rice University News AI-MI faculty member Keith Brown has been named Head of the Division of Materials Science & Engineering at Boston University, effective July 1, 2026.

An associate professor of mechanical engineering, materials science and engineering, and physics, Brown is a pioneer of “self-driving labs” that combine robotics, AI, and additive manufacturing to accelerate materials discovery — research directly aligned with AI-MI’s mission. He succeeds David Bishop, who led the division for 15 years. Keith Brown in his lab.

Photo: Boston University Source: https://www. bu. edu/eng/2026/06/10/keith-brown-to-lead-materials-science-engineering-division/ AI-MI Seminar Series: Digital Twins, AI-aided control and the Path to Scalable Quantum Hardware: From Sensing to Computing September 3 @ 10:00 am - 11:00 am 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.