College of Science & Engineering
Twin Cities
This group's general research interests are in the areas of artificial intelligence (AI) and machine learning (ML), where they focus on advancing foundations of AI/ML to solve challenging real-world problems with high societal impact. The overarching theme of this research program is AI to Accelerate Scientific Discovery and Engineering Design. Specific topics include:
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Probabilistic modeling (Gaussian processes, deep models, and their combination) over combinatorial structured data in small supervised data settings
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Combining domain knowledge and data to create structured models with uncertainty quantification
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Sequential decision-making under uncertainty for data acquisition to achieve target goals (e.g., design optimization, discovery, predictive models, decision policies) in a resource-efficient manner
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Applications: accelerate the discovery of nanoporous materials for sustainability applications (e.g., carbon capture and storage/separation of gases); accelerate the design of effective, safe, and low-cost drugs/vaccines; and design of high-performance and low-power hardware to overcome Moore’s law