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The NIEHS Superfund Research Program (SRP) is hosting a Risk e-Learning webinar series focused on using artificial intelligence (AI) and machine learning to advance environmental health research. The series will feature SRP-funded researchers, collaborators, and other subject-matter experts who aim to better understand and address environmental health issues by applying AI and machine learning approaches to complex issues.

Recent advances in AI and machine learning methods show promise to improve the accuracy and efficiency of environmental health research. Over the course of three sessions, presenters will discuss how they use AI and machine learning approaches to improve chemical analysis, characterize chemical risk, understand microbial ecosystems, develop technologies for contaminant removal, and more.


Session I — AI & ML Applications to Understand Chemical Mixtures, Properties, and Exposures and their Relationship to Human Health 
Monday, November 4, 2:00 - 4:00 PM ET
To register for the webinar, visit EPA's CLU-IN Training and Events webpage.

The first session will feature three presentations discussing the application of machine learning and artificial intelligence techniques to understand chemical exposures and effects on human health.

Presenters:

  • Naomi J. Halas, D.Sc., Ph.D., and Ankit Patel, Ph.D., Rice University
  • Jacob Kvasnicka, Ph.D., U.S. Environmental Protection Agency
  • Trey Saddler, M.S., NIEHS, Division of Translational Toxicology
  • Moderator: David M. Reif, Ph.D., NIEHS, Division of Translational Toxicology


Session II — ML & AI Applications to Environmental Engineering & Bioremediation
Wednesday, November 20, 2:00 - 4:00 PM ET
To register for the webinar, visit EPA's CLU-IN Training and Events webpage.

The second session will feature three speakers discussing how they apply machine learning and artificial intelligence to environmental engineering applications including detecting contaminants and cleaning up the environment using biosensors, microbiome compositions, and screening tools.

Presenters:

  • Kei-Hoi Cheung, Ph.D., Yale University School of Medicine
  • Mohammad Soheilypour, Ph.D., Nexilico Inc.
  • Paul Westerhoff, Ph.D., Arizona State University
  • Moderator: Rodrigo Rimando, U.S. Department of Energy


Session III — ML & AI Applications to Understand Omics, Metabolomics, & Immunotoxicity and Optimize Bioengineering Using Datasets, Models, and Mass Spectrometry
Friday, November 22, 12:00 - 2:00 PM ET
To register for the webinar, visit EPA's CLU-IN Training and Events webpage.

The third session will feature four speakers discussing how they apply machine learning and artificial intelligence tools to analyze mass spectrometry and microscopy data and optimize models for understanding metabolomics, metabolite pathways, and immunotoxicology.

Presenters:

  • Douglas Lauffenburger, Ph.D., MIT Department of Biological Engineering
  • Grace C.Y. Peng, Ph.D., Division of Discovery Science and Technology (Bioengineering), NIBIB and Trey Ideker, Ph.D., University of California San Diego
  • John Efromson, M.S., Ramona Optics
  • Moderator: Hunter Moseley, Ph.D., University of Kentucky