CU AI for Science Seminar - Dr. Kyunghyun Cho on Deep Learning for Molecular Design

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  • Опубликовано: 13 май 2024
  • The goal of the Cornell AI for Science Seminar Series is to bringing together the computational and scientific communities to understand advances and challenges at the frontier of AI for scientific discovery. In addition to senior speakers, the seminar features the research of Schmidt Futures AI for Science Postdoctoral researchers from multiple institutions. Seminars occur roughly biweekly on Fridays from 2:30-3:30pm EST. See our website for more information: science.ai.cornell.edu/
    Abstract: In this talk, I will describe machine learning paradigms that form a foundation on top of which we have built the lab-in-the-loop antibody design platform at Prescient Design, a Genentech Accelerator. These paradigms include multiobjective blackbox optimization and generative models.
    Bio: Kyunghyun Cho is a professor of computer science and data science at New York University and a senior director of frontier research at the Prescient Design team within Genentech Research & Early Development (gRED). He is also a CIFAR Fellow of Learning in Machines & Brains and an Associate Member of the National Academy of Engineering of Korea. He served as a (co-)Program Chair of ICLR 2020, NeurIPS 2022 and ICML 2022. He is also a founding co-Editor-in-Chief of the Transactions on Machine Learning Research (TMLR). He was a research scientist at Facebook AI Research from June 2017 to May 2020 and a postdoctoral fellow at University of Montreal until Summer 2015 under the supervision of Prof. Yoshua Bengio, after receiving MSc and PhD degrees from Aalto University April 2011 and April 2014, respectively, under the supervision of Prof. Juha Karhunen, Dr. Tapani Raiko and Dr. Alexander Ilin. He received the Samsung Ho-Am Prize in Engineering in 2021. He tries his best to find a balance among machine learning, natural language processing, and life, but almost always fails to do so.
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