WIT Webinar: "Machine Learning in Hydrology"

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The Centre for Water Informatics and Technology presents a virtual seminar titled: "Machine Learning in Hydrology" as part of its "Best of Water Systems Research" seminar series.

Wed, Sep 08 2021 to Wed, Sep 08 2021

Date: Wednesday, September 08, 2021

Time: 6:00 – 7:00 pm PKT

Speaker: Dr. Grey Nearing, Assistant Professor of Environmental Data Science, University of California Davis, and Visiting Researcher at Google Research.

Moderator: Dr. Talha Manzoor, Assistant Professor, WIT

Details and registration: https://wit.lums.edu.pk/BWSR2021

 

Abstract: Machine Learning (ML) applications in the hydrological sciences have accelerated rapidly in the past 3 years. I will give a brief overview of some of these applications that point toward what I see as a larger shift in focus within the community. This talk will cover technical details on applications of streamflow forecasting in particular, as well as results from other aspects of terrestrial modeling, including surface energy partitioning and carbon flux modeling (net ecosystem exchange). I will discuss briefly the state of physics-informed ML in the discipline and hypothesize what types of hybrid (physics + ML) applications we might see in the near future.

About the Speaker: Dr Grey Nearing is an Assistant Professor of Environmental Data Science at the University of California Davis, and a Visiting Researcher at Google Research. He was previously a member of hydrology modeling teams at NASA and the US National Center for Atmospheric Research (NCAR). Dr. Nearing's research is focused primarily on machine learning in hydrology and land surface modeling.

For details or queries, please contact Soban Hameed Saigol at soban.hameed@lums.edu.pk or 0332 4495057

Add to Calendar 2021-09-08 18:00:00 2021-09-08 19:00:00 WIT Webinar: "Machine Learning in Hydrology" Date: Wednesday, September 08, 2021 Time: 6:00 – 7:00 pm PKT Speaker: Dr. Grey Nearing, Assistant Professor of Environmental Data Science, University of California Davis, and Visiting Researcher at Google Research. Moderator: Dr. Talha Manzoor, Assistant Professor, WIT Details and registration: https://wit.lums.edu.pk/BWSR2021   Abstract: Machine Learning (ML) applications in the hydrological sciences have accelerated rapidly in the past 3 years. I will give a brief overview of some of these applications that point toward what I see as a larger shift in focus within the community. This talk will cover technical details on applications of streamflow forecasting in particular, as well as results from other aspects of terrestrial modeling, including surface energy partitioning and carbon flux modeling (net ecosystem exchange). I will discuss briefly the state of physics-informed ML in the discipline and hypothesize what types of hybrid (physics + ML) applications we might see in the near future. About the Speaker: Dr Grey Nearing is an Assistant Professor of Environmental Data Science at the University of California Davis, and a Visiting Researcher at Google Research. He was previously a member of hydrology modeling teams at NASA and the US National Center for Atmospheric Research (NCAR). Dr. Nearing's research is focused primarily on machine learning in hydrology and land surface modeling. For details or queries, please contact Soban Hameed Saigol at soban.hameed@lums.edu.pk or 0332 4495057 LUMS Drupal 8 adil.sarwar@lums.edu.pk Asia/Karachi public

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