Department news
AI-CLIMATE Study Published in Nature Communications
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Scholars from the National Artificial Intelligence Institute for Climate-Land Interactions, Mitigation, Adaptation, Tradeoffs and Economy (AI-CLIMATE) published a study demonstrating how knowledge-guided machine learning (KGML) can improve carbon cycle quantification in agroecosystems.
CS&E’s Vipin Kumar Serves as Key Partner on Great Lakes Water Innovation Engine
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Kumar’s group will bring the power of machine learning to optimize different steps involved in the treatment of waste water while recovering nutrients in an energy efficient manner.
Yao-Yi Chiang, Chang Ge Support NSF Convergence Accelerator Phase 1 Project at UMN
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The interdisciplinary team is developing Aquasense, a low-cost, compact, easy-to-use, rapid water quality sensor platform enabled by artificial intelligence (AI).
Yao-Yi Chiang Receives $3.2M in Funding to Leverage AI in Predicting Mineral Deposits
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Yao-Yi Chiang won two contracts from the Defense Advanced Research Projects Agency (DARPA) Critical Mineral Assessments with AI Support (CriticalMAAS) program (with the Information Sciences Institute and InferLink Corporation).
Chad Myers Harnesses AI to Improve Disease Prediction from Genetic Sequences
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The majority of genome-wide association studies focus on one-to-one relationships between genes and diseases. Myers’ work focuses on combinations of variants to better explain the relationship between a person’s gene’s and specific diseases.
Dan Knights Utilizes AI to Predict Emissions on Ships
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Shipping accounts for a significant fraction of the total global carbon emissions, and most ships in the ocean are not currently required to report their emissions or fuel efficiency. Knights’ work is intended to help paint a fuller picture of the actual shipping emissions for individual vessels.
Ju Sun Receives $4.5M in Funding for Medical AI Projects and Beyond
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Sun’s lab GLOVEX works at the intersection of machine and deep learning, numerical optimization, computer vision, and data science, with an aspiration to push the frontiers of AI in order to tackle major unsolved problems in science, engineering, and medicine.
GroupLens: A Human-Centered Approach to AI
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With the emergence of publicly-available AI tools like ChatGPT, the world is abuzz with the possibilities and risks that AI brings to the table. Embedding human values into AI systems is a necessary and complicated step that involves a variety of technical and societal factors.
Yoga Varatharajah Combats Clinician Burnout with Artificial Intelligence
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Working with clinicians at the U of M Medical School and Mayo Clinic, Varatharajah aims to develop AI methods to help interpret tests, optimize treatment decisions, and improve patient outcomes.
George Karypis Part of $4.5 Million Grant to Apply Machine Learning to Material Sciences
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The four-year project will establish foundational machine learning models that can be applied to material sciences.