Advancing Environmental Health Research with Artificial Intelligence and Machine Learning: Session II — ML & AI Applications to Environmental Engineering & Bioremediation

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.

In the second session ML & AI Applications to Environmental Engineering Contaminants & Bioremediation, invited presenters will discuss how they apply machine learning and artificial intelligence to environmental engineering applications including contaminants and bioremediation using biosensors, microbiome compositions, and screening tools.

To learn about and register for the other sessions in this webinar series, please see the SRP website.

Kei-Hoi Cheung, Ph.D., has an extensive history in data science, and has leveraged that expertise to lead natural language processing (NLP) projects in annotating, extracting, and retrieving environmental exposure data. He will present on the use of these NLP methods combined with ontologies in the in the context of scientific literature on emerging water contaminants.

Mohammad Soheilypour, Ph.D., will discuss the application of a suite of computational methods to identify and predict microbial metabolism of various chemical compounds, with a focus on gut and environmental microbiomes. Specifically, he will cover the potential application of machine learning models in this context and their integration with other computational methods to enhance both accuracy and utility.

Paul Westerhoff, Ph.D., will highlight the work of his research team utilizing and comparing two advanced multiple data imputation techniques, AMELIA and MICE algorithms, to fill gaps in sparse groundwater quality datasets to support State agencies in prioritizing future sampling activities. Historic water quality databases are often sparse due to financial budgets for collection and analysis, posing challenges in evaluating exposure or water treatment effectiveness — and this project aims to account for those by accurately assessing and managing risks associated with inorganic pollutants using this technology.

Speakers:

• 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

Kei-Hoi Cheung, PhD, Yale University School of Medicine (kei.cheung@yale.edu)
Kei-Hoi Cheung is a professor of Biomedical Informatics & Data Science at Yale School of Medicine and a professor of Biostatistics at Yale School of Public Health. His research interests include the semantic web, using ontologies to harmonize biomedical data and tools. In addition, he has been leading natural language processing (NLP) projects in annotating, extracting, and retrieving environmental exposure data from the literature as well as mining clinical text from the Veteran Administration's electronic medical records. Recently, he received an NIEHS grant entitled: “Accelerating Data and Metadata Standards in the Environmental Health Sciences Study of Emerging Water Contaminants.” Cheung completed his doctoral degree in computer science at the University of Connecticut.

Mohammad Soheilypour, PhD, Nexilico Inc (msoheilypour@nexilico.com)
Mohammad Soheilypour, Ph.D., is the co-founder and chief executive officer of Nexilico Inc., a biotechnology startup that uses computational biology and AI to address challenges in medicine and biotechnology. He is the principal investigator on four SBIR/STTR grants from NIH and the National Science Foundation. He earned his doctoral degree in computational biology at the University of California, Berkeley, and his research there, supported by the National Institutes of Health, formed the foundation for Nexilico's microbiome precision medicine technology.

Paul Westerhoff, PhD, Arizona State University (p.westerhoff@asu.edu)
Paul Westerhoff, Ph.D., is a Regents Professor in the School of Sustainable Engineering and the Built Environment at Arizona State University and the Fulton Chair of Environmental Engineering. He is the deputy director of the National Science Foundation’s Nanosystems Engineering Research Center for Nanotechnology Enabled Water Treatment, as well as an associate editor for the journal Environmental Science and Technology. He completed his doctoral degree in Civil, Architectural, and Environmental Engineering at the University of Colorado-Boulder.

Moderator:

Rodrigo Rimando, U.S. Department of Energy (rodrigo.rimando@em.doe.gov)
Rodrigo "Rod" V. Rimando, Jr. is Acting Director for the Office of Technology Development within the Office of Environmental Management (EM). Rod has over 36 years of nuclear experience that started in 1987, when he worked as a nuclear engineer at the Navy Department’s Charleston Naval Shipyard in South Carolina. He joined the Department of Energy in 1995 at the Savannah River Site, bringing with him his new expertise in nuclear facility decommissioning and environmental cleanup after he directed a large portfolio of cleanup projects in support of base closure. He transferred to EM headquarters in 2012, at which time he served as EM’s technical liaison to former Secretary Stephen Chu on Hanford’s Waste Treatment and Immobilization Plant. In 2016, when EM was reorganized, Rod served as the director of the newly formed Office of Technology Development for its first three years. Rod has a Bachelor of Science degree in Physics/Nuclear Physics from The Citadel, The Military College of South Carolina.

• Slide Presentation for Kei-Hoi Cheung, Ph.D., Yale University School of Medicine (1.26MB/PDF)
• Slide Presentation for Mohammad Soheilypour, Ph.D., Nexilico Inc (2.24MB/PDF)
• Slide Presentation for Paul Westerhoff, Ph.D., Arizona State University (5.64MB/PDF)

Webinar Slides and References:

• Slide Presentation for Kei-Hoi Cheung, Ph.D., Yale University School of Medicine (1.26MB/PDF)
• Slide Presentation for Mohammad Soheilypour, Ph.D., Nexilico Inc (2.24MB/PDF)
• Slide Presentation for Paul Westerhoff, Ph.D., Arizona State University (5.64MB/PDF)

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• These materials will be available by

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 November 20, 2024: Advancing Environmental Health Research with Artificial Intelligence and Machine Learning: Session II — ML & AI Applications to Environmental Engineering & Bioremediation

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