Physics to Machine Learning and Machine Learning Back to Physics

The speaker's flyer

Prof. Pierre Gentine
Columbia University
Monday December 19, 2022, 2 PM ET

Abstract:

Over the last couple of years, we have witnessed an explosion in the use of machine learning for Earth system science application ranging from Earth monitoring to modeling. Machine learning has shown tremendous success in emulating complex physics such as atmospheric convection or terrestrial carbon and water fluxes using satellite or high-fidelity simulations in a supervised framework. However, machine learning, especially deep learning, is opaque (the so-called black box issue) and thus a question remains: what (new) understanding have we really developed? I will here illustrate the value of machine learning for specific examples and some of the needed advances in machine learning to push climate science forward.

Biosketch:

Pierre Gentine is the Maurice Ewing and J. Lamar Worzel professor of geophysics in the departments of Earth and Environmental Engineering and Earth and Environmental Sciences at Columbia University. He studies the terrestrial water and carbon cycles and their changes with climate change. Pierre Gentine is the recipient of the National Science Foundation (NSF), NASA and Department of energy (DOE) early career awards, as well as the American Geophysical Union Global Environmental Changes Early Career, Macelwane medal and American Meteorological Society Meisinger award. He is the director of the new NSF Science and Technology Center (STC) for Learning the Earth with Artificial intelligence and Physics (LEAP), the largest funding mechanism of the NSF.

 

Webinar:

Event site: https://go.umd.edu/gentine
Zoom Webinar: https://go.umd.edu/gentinewebinar
Zoom Meeting ID: 913 6121 9329
Zoom password: essic
US Toll: +13017158592
Global call-in numbers: https://umd.zoom.us/u/aMElEpvNu

For IT assistance:
Cazzy Medley: cazzy@umd.edu

Resources:
Seminar schedule & archive: https://go.umd.edu/essicseminar
Seminar Google calendar: https://go.umd.edu/essicseminarcalendar
Seminar recordings on Youtube: https://www.youtube.com/user/ESSICUMD

Date

Dec 19 2022
Expired!
Category

Organizer

John Xun Yang
Email
jxyang@umd.edu