Home\Featured\Leveraging Machine Learning for Potable Reuse

Leveraging Machine Learning for Potable Reuse

When:
October 15, 2026 @ 1:00 pm – 2:00 pm America/New York Timezone
2026-10-15T13:00:00-04:00
2026-10-15T14:00:00-04:00
Leveraging Machine Learning for Potable Reuse

Machine learning (ML) provides a powerful framework for extracting actionable insight from complex water quality and operational datasets, but it remains underutilized in the water sector. Many reuse systems generate large volumes of monitoring, laboratory, and process data that are difficult to fully leverage using traditional analysis approaches. ML offers an opportunity to better understand system behavior, support predictive monitoring, and improve design and operational decision making. This presentation will provide water professionals with a practical foundation for understanding ML and evaluating where it can add value in reuse systems.

Case studies will demonstrate how ML can be integrated into existing workflows to enhance monitoring, design, and operational decision-making. Overall, this presentation provides attendees with practical tools and concrete examples to understand, evaluate, and apply ML in water reuse systems.

 

Register Now!

 

Moderator:

Andrea Odegard-Begay, PE, WRAZ President | Senior Associate, Hazen and Sawyer

 

Presenter:

Kyle Thompson, PhD, PE, Principal Reuse Technologist / Innovation Program Manager, Carollo Engineers

 

Event Fees
  • WateReuse Members: free
  • There is a $55 webcast fee for non-members

Professional Development Hours – 1 credit hour is available

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