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

Data science has become an essential discipline paving the path of LLNL's key program areas, and the Laboratory is home to some of the largest, most unique, and most interesting data and supercomputers in the world. The DSI acts as the central hub for all data science activity—in areas of artificial intelligence, big-data analytics, computer vision, machine learning, predictive modeling, statistical inference, uncertainty quantification, and more—at LLNL working to help lead, build, and strengthen the data science workforce, research, and outreach to advance the state-of-the-art of our nation's data science capabilities. Read more about the DSI.

Data Scientist Spotlight

Michael Ward

Michael Ward

Computer Scientist

Computer scientist Michael Ward strives to improve the world in any way he can. “My motivation is often driven by making things better, whether fixing something that’s broken, providing a better experience for a user, or refining something to be more capable or stable,” he explains. Ward works in LLNL’s Global Security Computing Applications Division on data science projects involving geospatial intelligence, object detection, and imagery processing. “The biggest challenge is keeping up with the pace of the field and supporting technology,” he states, noting that he continually enjoys tackling “tough and unique problems with some of the smartest minds in the field.” Before joining the Lab in 2018, Ward built software for sales training, banking, inventory, and telecommunications. He also taught college-level computer science for four years, and says the experience of finding ways to convey complex ideas and technologies to others has come in handy at the Lab. Ward earned bachelor’s and master’s degrees from the University of South Alabama.

New Research in AI: Human Vaccines Project

simulation of a computationally designed antibody interacting with the receptor binding domain of the spike protein of the SARS-CoV-2 virus
Simulation of a computationally designed antibody interacting with the receptor binding domain of the spike protein of the SARS-CoV-2 virus. Graphic courtesy of Dan Faissol/LLNL.

In a new three-year agreement with the HVP, LLNL will leverage its extensive knowledge in vaccine research response—most recently from designing new antibodies and antiviral drugs for COVID-19—its emerging work on AI and computational modeling of immune response and sepsis, as well as its computational infrastructure and scientists, to help accelerate development of vaccines and other medical countermeasures that could be protective against pandemic threats. A universal coronavirus vaccine or therapeutic would be effective against an entire family of related viruses, including variants of concern such as Delta, and available “off-the-shelf” for deployment in areas of high risk to prevent severe illness and avoid future pandemics.

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COVID-19 R&D: Computing responds to pandemic

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