DSI Council

The Council consults on LLNL’s overall data science strategy and helps to execute DSI activities.

Michael Goldman

Michael Goldman

DSI Director

In addition to serving as DSI Director, Michael is PI for several internal and external projects related to overhead imagery, machine learning, data compression, and system development. He is Associate Program Leader for the Collection Systems Innovation program in Global Security.

Timo Bremer

Peer-Timo Bremer

DSI Council Member

Peer-Timo holds a shared appointment at the Center for Applied Scientific Computing and the University of Utah. His research interests include large-scale machine learning, data analysis, medical image analysis, topology, and visualization.

Barry Chen

Barry Chen

DSI Council Member
Barry is the PI for several machine learning research projects devoted to the development of new neural network learning algorithms that address recurring challenges in scientific and security applications such as multimodal data and the scarcity of labeled data.
Goran Konjevod

Goran Konjevod

DSI Council Member

Goran works in LLNL’s Computational Engineering Division. As director of the Data Science Summer Institute from 2018 to 2022, Goran promotes the Council’s education and workforce initiatives.

Ana Kupresanin

Ana Kupresanin

DSI Council Member

Ana is deputy division leader of the Center for Applied Scientific Computing. Her expertise in uncertainty quantification, applied statistics, and machine learning support LLNL’s Weapons Complex and Integration program. Ana promotes sound statistical practices across LLNL programs.

Dan Merl

Dan Merl

DSI Council Member

Dan leads the Machine Intelligence Group in LLNL’s Center for Applied Scientific Computing. His research focuses on Bayesian inference, causal inference, experimental design, statistical computing, and probabilistic programming. Dan promotes computing and data initiatives on behalf of the Council.

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Michael Schneider

DSI Council Member

Michael leads a team within LLNL's Physics Division in science exploitation of the Large Synoptic Survey Telescope (LSST) for studying dark energy, dark matter, and the solar system. He serves as PI on internal and external projects in the areas of data analytics, computation, and sensor development.

Dan Faissol

Daniel Faissol

DSI Council Member Emeritus
Daniel is the PI on projects that combine simulation, real-world experiments, data-driven methods, and decision science to accelerate scientific discovery and provide novel solutions. His expertise includes agent-based modeling, stochastic optimization, deep reinforcement learning, and active learning.