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Presenter: Pierre Baldi, Distinguished Professor in the Department of Computer Science, Director of the Institute for Genomics and Bioinformatics, and Associate Director of the Center for Machine Learning and Intelligent Systems at the University of California Irvine.
Abstract: I will describe several applications of AI to problems in biomedicine developed in my laboratory, from the molecular level to the patient level using omic data, imaging data, clinical data, and beyond. For instance, I will show how deep learning methods can be used to:
(1) study circadian rhythms at the molecular level; (2) detect and segment polyps in real time in colonoscopy videos; and (3) predict post-operative adverse outcomes. I will discuss the opportunities and challenges for developing, integrating, and deploying AI in the first AI-driven hospital of the future.
Bio: Pierre Baldi earned MS degrees in Mathematics and Psychology from the University of Paris, and a PhD in Mathematics from the California Institute of Technology. He is currently Distinguished Professor in the Department of Computer Science, Director of the Institute for Genomics and Bioinformatics, and Associate Director of the Center for Machine Learning and Intelligent Systems at the University of California Irvine. The long term focus of his research is on understanding intelligence in brains and machines.He has made several contributions to the theory of AI and deep learning,and developed and applied AI and deep learning methods across the natural sciences, to address problems in physics (e.g., exotic particle detection), chemistry (e.g., reaction prediction), and bio-medicine(e.g., biomedical imaging analysis). He recently published his fifth book: Deep Learning in Science, Cambridge University Press (2021). His honors include the 1993 Lew Allen Award at JPL, the 2010 E. R. Caianiello Prize for research in machine learning, and election to Fellow of the AAAS, AAAI, IEEE, ACM, and ISCB.