UChicago PME research in AI is centered around three broad goals
AI-guided design-build-test-learn loops and/or autonomous discovery (“self-driving labs”)
UChicago PME researchers are augmenting traditional theoretical, computational, and experimental modes of inquiry with AI to massively accelerate molecular modeling and simulation, design new molecules, proteins, drugs, and quantum materials with higher efficiency and accuracy, and develop self-driving labs combining AI and automated robotics.
(PME faculty currently engaged in this area include Junhong Chen, Laura Gagliardi, Margaret Gardel, Liang Jiang, Andrew Ferguson, Y. Shirley Meng, Samantha Riesenfeld, Sihong Wang)
AI-guided design-build-test-learn loops and/or autonomous discovery (“self-driving labs”)
UChicago PME researchers are augmenting traditional theoretical, computational, and experimental modes of inquiry with AI to massively accelerate molecular modeling and simulation, design new molecules, proteins, drugs, and quantum materials with higher efficiency and accuracy, and develop self-driving labs combining AI and automated robotics.
(PME faculty currently engaged in this area include Junhong Chen, Laura Gagliardi, Margaret Gardel, Liang Jiang, Andrew Ferguson, Y. Shirley Meng, Samantha Riesenfeld, Sihong Wang)
Development of AI-enabled algorithms and computing hardware
UChicago PME researchers are developing new AI and ML algorithms (including eXpalinable AI and physics-aware AI) to extract patterns and correlations in high-dimensional complex biological data sets, design new molecules, proteins, and reticular materials for carbon capture and catalytic applications, and enable new quantum technologies. They are also working on the development of novel electronics (e.g., neuromorphic computing) that can serve as the hardware for implementing AI and ML with lower power consumption and lower carbon emissions.
(UChicago PME faculty currently engaged in this area include Chibueze Amanchukwu, Andrew Ferguson, Rama Ranganathan, Sihong Wang)
Collaborations and Opportunities in AI
UChicago Pritzker Molecular Engineering researchers collaborate with colleagues at the University of Chicago, at Argonne National Laboratory, and at more than twenty other research institutions. UChicago PME also provides unique opportunities to early-career scientists and engineers who wish to advance AI methods and applications in the domains of immunoengineering, materials systems, and quantum engineering.
Generative AI in Science and Research – Andrew Ferguson
