Team - ROME - Reduced modeling with extreme data

Benjamin Peherstorfer

Lead PI

New York University, Courant Institute

scientific machine learning model reduction computational statistics

Georg Stadler

Co-Lead PI

New York University, Courant Institute

high-performance computing optimization extreme events

Julie Bessac

Co-PI

National Renewable Energy Laboratory

statistical modeling in-situ data analysis

Qi Lei

Co-PI

New York University, Courant Institute and Center for Data Science

distributed machine learning data privacy theory of machine learning

Daniel O'Malley

Co-PI

Los Alamos National Laboratory

computational methods for subsurface flow and transport

Elizabeth Qian

Co-PI

Georgia Tech, Aerospace Engineering and Computational Science and Engineering

uncertainty quantification data-driven reduced modeling multifidelity methods

Ashesh Sharma

Co-PI

National Renewable Energy Laboratory

large-scale and high-performance computing wind farm modeling

Tomoki Koike

PhD student

Georgia Tech, Aerospace Engineering and Computational Science and Engineering

data-driven reduced modeling

Mingxin Li

PhD student

New York University, Courant Institute

reduced modeling rare-event simulation

Agnese Marcato

PostDoc

Los Alamos National Laboratory

computational methods for subsurface flow and transport

Prakash Mohan

PostDoc

National Renewable Energy Laboratory

large-scale and high-performance computing wind farm modeling

Aleksandra Atanasova Pachalieva

PostDoc

Los Alamos National Laboratory

computational methods for subsurface flow and transport

Meet the team of ROME

Tomoki Koike

Mingxin Li

Agnese Marcato