WaterGPT: Tailored AI for Water Engineering, Learning & Net-Zero Strategies

Webinar Summary

In this talk, we’ll present recent research on designing and benchmarking custom language models tailored to water environmental research, education and applications, streamlining literature reviews, data extraction, and knowledge sharing. We’ll showcase two research topics: one using literature-mining techniques to quantify greenhouse gas (GHG) emissions for mitigation strategies, and another applying machine learning models to optimize wastewater facility operations.

Webinar Speaker

Dr. Jason Ren is a professor in the Civil and Environmental Engineering Department and the Andlinger Center for Energy and the Environment at Princeton University. His research focuses on water resource recovery, decarbonization, and digitalization. He has authored more than 300 publications, one book, and co-founded two startups with students. He has received numerous awards including the AEESP Frontier in Research Award, the Water Research Foundation Paul Busch Award, and the ASCE Huber Research Prize. Jason is an associate editor of ACS Journal ES&T and ES&T Letters.

Webinar Format

This webinar will include a moderated Q and A session following the speaker’s presentation. The session is open to environmental engineering and science professionals across all sectors and career stages. Our objective is to offer special insights on leading edge solutions for graduate and undergraduate students as well as early to mid-career environmental professionals who are considering specialty certification.

AAEES Board Certified Individuals: Attend this event and earn 1.5 PDHs towards your PDH requirements for maintaining your specialty certification.

This event is part of the AAEES AI Webinar Series.  Click here for more information.

Click here to register for this event.