Accelerating next-generation materials research with AI.
The Artificial Intelligence Materials Institute is a collaboration between
Partnerships
Our 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.
To support this work, AI-MI plans to create the AI Materials Science Ecosystem (AIMS-EC) – an open, cloud-based portal that integrates a science-ready large language model with data from experiments, simulations, images and scientific literature. Using AIMS-EC, the institute will discover 2D moiré structures for robust qubits, learn descriptors that can guide the design of new superconductors, discover new functional soft materials and mixtures and identify functional peptides for the removal of microplastics from the environment.
Moreover, AI-MI will accelerate how materials are made using data-driven optimization of film growth and self-driving labs. Through partnerships with high schools, universities, and industry, AI-MI will educate and train students at all levels and open new career pathways at the intersection of AI and physical sciences.
“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
5
Top Research
Universities
18
Key Investigators
20
Million
in support from NSF
and Intel
25
Collaborators
5
Top Research
Universities
18
Key
Investigators
20
Million
in support from
NSF & Intel
25
Collaborators
Leadership Team
Eun-Ah Kim
PI, Cornell University
Expert in the physics of quantum materials and in application of AI to large and complex data from quantum materials.
Leslie Schoop
Co-PI, Princeton
Expert in quantum chemistry and topological materials.
Kilian Weinberger
Co-PI, Cornell University
Expert in machine learning and its applications in computer vision, natural language processing, and scientific discovery.
Faculty Members
Nicholas Abbott
Senior Personnel, Cornell University
Expert in soft functional materials, and the integration of computational and AI methods into soft matter experimentation.
B. Andrei Bernevig
Senior Personnel, Princeton
Expert in theoretical condensed matter physics.
Adam Braunschweig
CUNY
Expert in nanotechnology and organic chemistry, with a focus on glycobiology, nanolithography, biomaterials, and mechanochemistry.
Keith Brown
Senior Personnel, Boston University
Expert in hierarchical soft matter, autonomous experimentation, and scanning probe techniques.
Anil Damle
Senior Personnel, Cornell University
Expert in numerical linear algebra, computational quantum chemistry, computational statistics, and fast algorithms.
Peter Frazier
Senior Personnel, Cornell University
Expert in AI-based experimental design for materials design, including Bayesian optimization, multi-armed bandits, and active learning
Carla Gomes
Senior Personnel, Cornell University
Expert in AI, especially, large-scale knowledge representation, reasoning, and machine learning for scientific discovery.
Kin Fai Mak
Senior Personnel, Cornell University
Expert in devices and heterostructures based on 2D quantum materials, and their characterization.
Darrell Schlom
Senior Personnel, Cornell University
Expert in oxide molecular beam epitaxy based thin film growth. co-Director of Materials Innovation Platform PARADIM.
Jennifer Sun
Senior Personnel, Cornell University
Expert in developing computer vision and machine learning methods for workflows that require expert-in-the-loop interactions.
Fengqi You
Senior Personnel, Cornell University
Expert in advanced computational models, optimization and machine learning for smart manufacturing, energy systems, and sustainability.
Zhigang Zhu
CUNY
Expert in computer vision, machine learning, human computer interaction, augmented reality, and assistive technology.
Connect with us
Follow along as we accelerate the discovery of next-generation materials essential for energy, sustainability and quantum technologies.