• Michelle Gill: AI-Assisted Drug Discovery, NVIDIA, Biofoundation Models, Creating Applied Research Teams | Learning from Machine Learning #8

  • 2024/01/11
  • 再生時間： 1 時間 6 分
  • ポッドキャスト

Michelle Gill: AI-Assisted Drug Discovery, NVIDIA, Biofoundation Models, Creating Applied Research Teams | Learning from Machine Learning #8

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  • This episode features Dr. Michelle Gill, Tech Lead and Applied Research Manager at NVIDIA, working on transformative projects like BioNemo to accelerate drug discovery through AI. Her team explores Biofoundation models to enable researchers to better perform tasks like protein folding and small molecule binding.

    Michelle shares her incredible journey from wet lab biochemist to driving cutting edge AI at NVIDIA. Michelle discusses the overlap and differences between NLP and AI in biology. She outlines the critical need for better machine learning representations that capture the intricate dynamics of biology.

    Michelle provides advice for beginners and early career professionals in the field of machine learning, emphasizing the importance of continuous learning and staying up to date with the latest tools and techniques. She also shares insights on building successful multidisciplinary teams

    After hearing her fascinating PyData NYC keynote, it was such an honor to have her on the show to discuss innovations at the intersection of biochemistry and AI.

    References and Resources

    https://michellelynngill.com/

    Michelle Gill - Keynote - PyData NYC https://www.youtube.com/watch?v=ATo2SzA1Pp4

    AlexNet

    AlphaFold - https://www.nature.com/articles/s41586-021-03819-2

    OpenFold - https://www.biorxiv.org/content/10.1101/2022.11.20.517210v1

    BioNemo - https://www.nvidia.com/en-us/clara/bionemo/

    NeurIPS - https://nips.cc/

    Art Palmer - https://www.biochem.cuimc.columbia.edu/profile/arthur-g-palmer-iii-phd

    Patrick Loria - https://chem.yale.edu/faculty/j-patrick-loria

    Scott Strobel - https://chem.yale.edu/faculty/scott-strobel

    Alexander Rives - https://www.forbes.com/sites/kenrickcai/2023/08/25/evolutionaryscale-ai-biotech-startup-meta-researchers-funding/?sh=648f1a1140cf

    Deborah Marks - https://sysbio.med.harvard.edu/debora-marks

    Resources to learn more about Learning from Machine Learning

    • https://www.linkedin.com/company/learning-from-machine-learning
    • https://mindfulmachines.substack.com/
    • https://www.linkedin.com/in/sethplevine/
    • https://medium.com/@levine.seth.p
    続きを読む 一部表示

あらすじ・解説

This episode features Dr. Michelle Gill, Tech Lead and Applied Research Manager at NVIDIA, working on transformative projects like BioNemo to accelerate drug discovery through AI. Her team explores Biofoundation models to enable researchers to better perform tasks like protein folding and small molecule binding.

Michelle shares her incredible journey from wet lab biochemist to driving cutting edge AI at NVIDIA. Michelle discusses the overlap and differences between NLP and AI in biology. She outlines the critical need for better machine learning representations that capture the intricate dynamics of biology.

Michelle provides advice for beginners and early career professionals in the field of machine learning, emphasizing the importance of continuous learning and staying up to date with the latest tools and techniques. She also shares insights on building successful multidisciplinary teams

After hearing her fascinating PyData NYC keynote, it was such an honor to have her on the show to discuss innovations at the intersection of biochemistry and AI.

References and Resources

https://michellelynngill.com/

Michelle Gill - Keynote - PyData NYC https://www.youtube.com/watch?v=ATo2SzA1Pp4

AlexNet

AlphaFold - https://www.nature.com/articles/s41586-021-03819-2

OpenFold - https://www.biorxiv.org/content/10.1101/2022.11.20.517210v1

BioNemo - https://www.nvidia.com/en-us/clara/bionemo/

NeurIPS - https://nips.cc/

Art Palmer - https://www.biochem.cuimc.columbia.edu/profile/arthur-g-palmer-iii-phd

Patrick Loria - https://chem.yale.edu/faculty/j-patrick-loria

Scott Strobel - https://chem.yale.edu/faculty/scott-strobel

Alexander Rives - https://www.forbes.com/sites/kenrickcai/2023/08/25/evolutionaryscale-ai-biotech-startup-meta-researchers-funding/?sh=648f1a1140cf

Deborah Marks - https://sysbio.med.harvard.edu/debora-marks

Resources to learn more about Learning from Machine Learning

  • https://www.linkedin.com/company/learning-from-machine-learning
  • https://mindfulmachines.substack.com/
  • https://www.linkedin.com/in/sethplevine/
  • https://medium.com/@levine.seth.p
続きを読む 一部表示

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