Raffaele Marino

Raffaele Marino
During his doctoral studies he worked on the characterization of turbulence in the interplanetary space, obtaining a joint PhD from the University of Calabria (IT) and the University of Nice-Sophia-Antipolis (FR). He was postdoctoral fellow at the Italian National Institute for Astrophysics (IT) and the National Center for Atmospheric Research (U.S.), where he developed research on geophysical turbulence gaining expertise on high performance computing. While in the United States he was as well affiliate research associate at the Space Sciences Laboratory of the University of California Berkeley. He is currently CNRS scientist and adj. professor at the École Centrale de Lyon (FR), where he conducts research on turbulence, waves, nonlinear phenomena in fluids of geophysical interest and space plasmas.

Enrico CamporealePresident-Elect
Enrico Camporeale

Enrico Camporeale graduated in space plasma physics from the Queen Mary University of London. He has worked at the Los Alamos National Laboratory and the Dutch National Center for Mathematics and Computer Science (CWI). He is currently a research associate with the University of Colorado Boulder, affiliated with the NOAA Space Weather Prediction Center, in Boulder, Colorado and a senior lecturer in Digital Environment at the Queen Mary University of London. His research activities focus on the use of machine learning and artificial intelligence to improve the forecasting capabilities of space weather models and on data-driven discovery of space physics. He is the founding Editor-in-Chief of the AGU journal JGR: Machine Learning and Computation.

Brad Weir

Brad Weir

Brad Weir is a scientist at NASA Goddard Space Flight Center and Morgan State University through the GESTAR II cooperative agreement. He is the lead developer of NASA's Goddard Earth Observing System (GEOS) Constituent Data Assimilation System (CoDAS), a state-of-the-art statistical method for estimating atmospheric trace gas abundances based on satellite observations. His research focuses on developing and applying mathematical and statistical methods to understand the integrated Earth system with a focus on the carbon cycle. Prior to working at NASA Goddard, he was a graduate student at the University of Arizona and a post-doctoral researcher at the College of Earth, Ocean, and Atmospheric Sciences at Oregon State University.

Juan Restrepo

Juan M. Restrepo

Juan M. Restrepo specializes in non-equilibrium statistical and deterministic dynamics and works on methodologies that incorporate data and physical models as well as artificial intelligence methods for classification and reduction. He has a track record in research in estimation theory and data assimilation as well as sampling in Bayesian problems. Among other projects, he is working on interpretable artificial intelligence methods, high performance ensemble computing, sampling methods. He also works on time dependent probabilistic methods in statistical physics. His applications research spans systems biology, electric grids, ocean transport, climate dynamics, epidemics, coastal resilience, oil spills and nearshore processes. He holds a Joint Faculty appointment in the Mathematics Department at the University of Tennessee, Knoxville,  and an adjunct faculty position in the Mathematics Department at Oregon State University. Prior to ORNL he was a faculty member at Oregon State University, and at the University of Arizona.

Past Presidents

  • 1998-2002 John Rundle
  • 2002-2004 Christopher Barton
  • 2004-2008 A. Surjalal Sharma
  • 2008-2012 Shaun Lovejoy
  • 2012-2014 Daniel Schertzer
  • 2014-2016 Andrea Donnellan
  • 2016-2018 Annick Pouquet
  • 2019-2021 Sarah Tebbens

Past Secretaries

  • 1998-2002 Seth Veitzer
  • 2002-2004 Bruce Malamud
  • 2004-2008 --
  • 2008-2012 James Wanliss
  • 2012-2014 Alin Carsteanu
  • 2014-2018 Joern Davidsen
  • 2019-2021 Raffaele Marino
  • 2021-2023 Dallas Foster