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Christine Kirkpatrick, M.A.S.

Christine Kirkpatrick leads the San Diego Supercomputer Center’s (SDSC) Research Data Services division, which manages large-scale infrastructure, networking, and services for research projects of regional and national scope. Her research is in data-centric AI, working at the intersection of ML and FAIR, with a focus on making AI more efficient to save on power consumption and 'time to science'. In addition to being PI of the EarthCube Office (ECO), Kirkpatrick founded the GO FAIR US Office, is PI of the West Big Data Innovation Hub, is on the Executive Committee for the Open Storage Network, and Co-PI of the NSF-funded Transboundary Groundwater Resiliency Research (TGRR) network. Christine serves as a member for The National Academies of Sciences, Engineering, and Medicine on their Board on Research Data and Information (BRDI) to improve the stewardship, policy and use of digital data and information for science and the broader society. She serves as the Secretary General of the International Science Council's Committee on Data (CODATA), co-Chairs the FAIR Digital Object Forum, is on the Advisory Board for the Helmholtz Federated IT Services (HIFIS), and served on the National Academies of Sciences’ U.S. National Committee for the Committee on Data.

Marty Kandes

Computational & Data Science Research Specialist

Marty Kandes a Computational and Data Science Research Specialist in the High-Performance Computing User Services Group at SDSC. He currently helps manage user support for Comet — SDSC’s largest supercomputer. Marty obtained his Ph.D. in Computational Science in 2015 from the Computational Science Research Center at San Diego State University, where his research focused on studying quantum systems in rotating frames of reference through the use of numerical simulation. He also holds an M.S. in Physics from San Diego State University and B.S. degrees in both Applied Mathematics and Physics from the University of Michigan, Ann Arbor. His current research interests include problems in Bayesian statistics, combinatorial optimization, nonlinear dynamical systems, and numerical partial differential equations.