Our mission at the Data Science Institute (DSI) is to enable excellence in data science research and applications across LLNL's core missions.

Data Scientist Spotlight

Mary Silva

Mary Silva

Data Scientist

With an M.S. in Statistics and Applied Math from UC Santa Cruz, Mary Silva knows firsthand how the Lab’s multidisciplinary approach to teamwork can elevate everyone involved. “Even without an extensive background in biology, I can contribute to vaccine development and target identification while utilizing domain experts’ knowledge to interpret models and results. These experiences have inspired me to take computational biology courses. A data scientist is forever a student,” she explains. A former DSSI intern, Silva joined LLNL in 2020 and today works on active learning and Bayesian spatial models for rapid design of COVID-19 antibodies, as well as enhancing machine learning models through the multi-institutional Scalable Precision Medicine Open Knowledge Engine (SPOKE) project. As a mentor, she helps students improve their weaknesses. For instance, she says, “If a student doesn’t have public speaking confidence, I can give them opportunities to present their work to an audience.” Silva also co-organizes the Lab’s Women in Data Science (WiDS) event and datathon challenge. “I found my Lab internship by attending WiDS Livermore with my professor, and the ability to socialize and network with LLNL researchers kicked off my career,” she states.

New Research in AI: HPC and CogSim Aid Fusion Ignition Breakthrough

artist's rendering of lasers hitting the target

On December 5th, the research team at LLNL's National Ignition Facility (NIF) achieved a historic win in energy science: for the first time ever, more energy was produced by an artificial fusion reaction than was consumed—3.15 megajoules produced versus 2.05 megajoules in laser energy to cause the reaction. High-performance computing was key to this breakthrough (called ignition), and HPCwire recently had the chance to speak with Brian Spears, deputy lead modeler for inertial confinement fusion (ICF) at the NIF, about HPC’s role in making this fusion ignition a reality. Spears said there were essentially two pieces to their predictive capability. First, their fundamental design capability—using hundreds of thousands of lines of radiation hydrodynamics code to run massive simulations of fusion reactions on leadership-class supercomputers. Second: cognitive simulation, or CogSim. Read more at HPCwire.

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