Noah Flynn

News

I wrote a book with Manning Publications! I'm happy to announce that "Machine Learning for Drug Discovery" is now available via Manning's Early Access Program (MEAP)! Check it out here and use code "au35fly" for a 35% discount!

The search for novel, improved therapeutics is an important problem and impacts all of our lives. "Machine Learning for Drug Discovery" is an informative deep dive that aligns machine learning and deep learning theory with contemporary applications in drug discovery. While a cliché, it is nevertheless true: this is the book I wish I had available to me when I started my graduate studies and early career in industry. Each chapter is structured around real-world scenarios and iteratively builds up a solution with code provided every step of the way. By the end, you'll have the agency to explore, apply, replicate, and improve upon innovations and publications at the intersection of machine learning and drug discovery. Both seasoned researchers and newcomers welcome -- no prior background in chemistry or machine learning is necessary!

With MEAP, the first five chapters are immediately available along with access to a forum where we can directly discuss the projects and material. You'll also have first access to later chapters as they are progressively released, accompanying your learning pace. Next chapter coming soon, where we'll replicate the findings of a recent high impact paper! Feel free to browse (or contribute) to the official code repository, though keep in mind that significant development is still underway! Happy learning!

Bio

Hello! I'm Noah, a research scientist at Amazon within the Artificial General Intelligence (AGI) organization. My focus is on applications of large language models in dialogue systems, multilingual natural language understanding, and graph machine learning for natural language processing.

I also maintain expertise and interest in advancing the field of machine learning and drug discovery. Prior to Amazon, I earned a PhD in Computational Biology at Washington University School of Medicine in St. Louis within the Department of Pathology & Immunology (Thesis). My research focused on applications of deep learning to improving drug toxicity screening and safety assessment. For example, detecting signals from electronic health records that relate to drug-drug interactions and modeling drug metabolism networks to predict vectors of drug toxicity, formation of reactive chemical species, and likelihood of adverse drug reactions. As part of my research, I served as a core maintainer of XenoSite and I launched the XenoNet Web Server. XenoSite is a prediction web service for small molecule biochemistry that hosts an online collection of metabolism and reactivity mathematical models that systematically summarize the data from thousands of papers into a condensed and useable computational tool that predicts adduction and potential toxicity of molecules.

If you are looking for a collaborator or simply want to connect with someone who shares your passion for using technology to make a positive impact in the world, please don't hesitate to get in touch.

I am in the process of updating my website and have a few upcoming projects to announce heading into 2023 Q3, so feel free to keep checking in!

Publications

Most recent publications on Google Scholar.
^‡ indicates equal contribution.

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Vitæ

Full Resume in PDF.

• Amazon Jun 2021 - now

  Research Scientist II
  Alexa AI
• Merck (MSD) May 2019 - Aug 2019

  Machine Learning Intern
  Modeling & Informatics
• WUSTL Aug 2017 - Jun 2021

  Ph.D. Student
  Computational Biology
  Department of Pathology & Immunology
• National Center for Supercomputing Applications May 2016 - May 2017

  Computational Research Fellow
  
• UIUC College of Engineering Apr 2016 - Jul 2017

  Director
  Engineering Open House
• AbbVie Nov 2015 - May 2017

  Software Engineer, Intern
  Platform Informatics & Knowledge Management
• Seitz Materials Research Lab Dec 2014 - Aug 2016

  Research Assistant
  John Rogers Group
• Institute for Genomic Biology Feb 2014 - Sep 2015

  Research Assistant
  Biosystems Design Group (iGEM)
• University of Illinois at Urbana-Champaign 2013 - 2017

  B.Sc. Student
  Bioengineering
  Computer Science (Minor)

Website Design