The past few years have witnessed the transformative impact of artificial intelligence (AI) and machine learning (ML) in many applications, such as speech and image recognition, consumer behavior prediction, and self-driving cars, primarily driven by the tremendous growth in data collection and storage capabilities as well as in computing power. This talk will review the exciting opportunities in applying AI/ML and data analytics to solving environmental problems, and to identify research priorities our community should focus on in the near future. Examples of topics to be covered include developing quantitative structure-activity relationships for biotic/abiotic reactivity, adsorption, uptake, treatment, and toxicity of organic and inorganic compounds; big data-informed water/wastewater infrastructure management; characterize sources of pollution and model emissions of various contaminants in the air, water, soil and sediment; model and predict contaminant levels and conduct risk assessment in natural and engineered systems; predict and optimize treatment efficiencies in various treatment and remediation processes; and monitor and predict nutrients and contaminants levels in different environmental compartments.

Applications of artificial intelligence, machine learning, and data analytics in environmental science and engineering: Current status and future directions

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.