The Computational Social Science (CSS) Working Group hosted a special event with LEAP, Learning the Earth with Artificial Intelligence and Physics, the recently launched NSF STC here at Columbia University. Panelists discussed the core areas of LEAP’s research, why education, equity, and bi-directional knowledge transfer are core to LEAP’s mission, why climate modeling may be important for your scholarship, and the open-access data and computing platform, LEAPangeo, that we hope will transform climate data science. In addition to introducing LEAP to the broader Columbia community, the discussion also set a foundation for LEAP engagement, collaboration, and data and knowledge sharing generally.

See the event recording below.

CSS Co-Chairs:

Presenting LEAP Team Members

Courtney D. Cogburn
Associate Profession of Social Work, LEAP Chief Equity Officer & Knowledge Transfer Director

Presented remotely

Courtney D. Cogburn is an associate professor at the Columbia University School of Social Work and faculty of the Columbia Population Research Center and Data Science Institute where she co-chairs the Computational Social Science Working Group. She employs a transdisciplinary approach to improve the characterization and measurement of racism, and in examining the role of racism in the production of racial inequities in health. Her work also explores media as a social stressor that contributes to racial inequities in health. She also works at the intersection of emerging technology and social justice. She completed postdoctoral training at Harvard University in the RWJF Health & Society Scholar Program and at the Institute for Social Research at the University of Michigan. She received her Ph.D. in Education and Psychology and an MSW from the University of Michigan and completed her BA in Psychology at the University of Virginia.

Pierre Gentine
Professor of Geophysics, LEAP Director

Presented in-person

Pierre Gentine investigates the continental hydrologic cycle using multi scale modeling and big data (machine learning, remote sensing, high-resolution turbulent simulations) in the context of rising CO2 concentrations. Gentine hopes to answer questions such as what will be the future of droughts and extreme dryness/precipitations, and how will they impact agricultural production? Pierre Gentine received his undergraduate degree from SupAéro, the French National Aeronautical and Space Engineering School in Applied Mathematics in Toulouse, France. He obtained a MSc and PhD in civil and environmental engineering from Massachusetts Institute of Technology (MIT) in 2006 and 2010, respectively. He joined the faculty of the Department of Applied Mathematics and Applied Physics at Columbia Engineering in 2010.

Dave Lawrence 
NCAR Model Development Liaison, LEAP Senior Scientist, and Section Head at National Center for Atmospheric Research – NCAR

Presented remotely

Dave is a Scientist in NCAR’s Climate and Global Dynamics Laboratory.  He received his PhD from the University of Colorado in Atmospheric and Ocean Sciences in 1999, before doing a postdoc at the University of Reading in the UK.  He came to NCAR in 2003. His main research interests center around land surface processes and climate change with a particular emphasis on research into Arctic terrestrial climate system feedbacks, including the impact of permafrost degradation on carbon, water, and energy cycles, and into land-use change impacts on climate.  He is a co-lead of the Community Terrestrial Systems Model (CTSM), an effort to unify land modeling across NCAR and the broader research community.  He is co-chair of the Land Use Model Intercomparison Project (LUMIP) for CMIP6 and co-chair of the Permafrost Carbon Network Model Integration group.  

Tian Zheng
Professor & Chair of Statistics, LEAP Chief Convergence Officer & Education Director

Presented in-person

Tian Zheng is currently Professor and Department Chair of Statistics at Columbia University. She obtained her Ph.D. from Columbia in 2002. In her research, she develops novel methods for exploring and understanding patterns in complex data from different application domains such as biology, psychology, climatology, and etc. Her current projects are in the fields of statistical machine learning, spatiotemporal modeling, and social network analysis, collaborating with ecologists and earth scientists. 

Details & Recording

Tuesday, April 26, 2022 (2:00 PM – 3:00 PM ET) – HYBRID

This event was held on Zoom and at the Columbia Business School (Kravis Room 690)