BIDS Machine Learning and Science Forum — Data-driven and data-assisted modeling for applications in fluid dynamics and geophysics

ML&Sci Forum

October 11, 2021
11:00am to 12:00pm
Virtual Participation

BIDS Machine Learning and Science Forum
Date: Monday, October 11, 2021
Time: 11:00 AM - 12:00 PM Pacific Time
Location: Participate remotely using this Zoom link 

Data-driven and data-assisted modeling for applications in fluid dynamics and geophysics

Speaker: Jaideep Pathak, Postdoctoral Researcher, NERSC
Abstract: Advances in the field of Machine Learning (ML) have the potential to be important in developing tools for scientific disciplines such as climate modeling, weather prediction, and computational fluid dynamics. In this talk I will consider some aspects of purely data-driven models as well as techniques to construct hybrid models that combine a physics-based numerical model with ML. Purely data-driven models of spatiotemporal dynamics can often be limited by computational resource or data availability constraints. Using ML in conjunction with a physics-based numerical model has the potential to solve some of the issues associated with purely data-driven models. I will demonstrate some techniques for building hybrid physics-ML models using a few examples from computational fluid dynamics and real-world problems in numerical weather prediction.

The BIDS Machine Learning and Science Forum meets biweekly to discuss current applications across a wide variety of research domains in the physical sciences and beyond. Hosted by BIDS Affiliates Uroš Seljak (professor of Physics at UC Berkeley) and Ben Nachman (physicist at Lawrence Berkeley National Laboratory), these active sessions bring together domain scientists, statisticians, and computer scientists who are either developing state-of-the-art methods or are interested in applying these methods in their research.  To receive email notifications about upcoming meetings, or to request more information, please contact the organizers at berkeleymlforum@gmail.comAll interested members of the UC Berkeley and Berkeley Lab communities are welcome and encouraged to attend. 


Jaideep Pathak

Postdoctoral Researcher, NERSC

Jaideep Pathak is a postdoctoral researcher at the National Energy Research Scientific Computing Center (NERSC), Lawrence Berkeley National Laboratory (LBNL). His research interests are broadly within the areas of machine learning, high performance computing, computational fluid dynamics, and earth sciences.