In April 2023, Brian Giera was named the new director of the Data Science Institute (DSI). In this role, Giera, a materials and manufacturing researcher in LLNL’s Engineering Directorate, will oversee the DSI’s efforts to strengthen the Lab’s data science workforce pipeline, research directions, and community outreach.
“The DSI is a thriving organization, so I am excited for the impact we will have given all the positive momentum,” says Giera. Outgoing director Michael Goldman adds, “Brian will lead the DSI into a promising new phase, given how tremendously the Lab’s workforce and capabilities have grown since we established the DSI in 2018.”
Giera joined LLNL in 2014 as a postdoctoral researcher and currently leads the Analytics for Advanced Manufacturing group in the Lab’s Materials Engineering Division. He has worked on a variety of machine learning projects such as optimizing the production of carbon capture technology, quality detection of metal additive manufacturing, and speeding up the time to deployment in the advanced manufacturing development cycle. A recipient of multiple LLNL Diversity & Inclusion Director’s Awards, Giera holds a PhD in Chemical Engineering from the University of California at Santa Barbara. Below he considers a few questions about data science at LLNL and the DSI’s future.
How has your career intersected with data science?
I started data science research during the 25% self-directed time that the Lab gives to postdocs. I was investigating ways to extract insights from advanced manufacturing sensor data. I suspected the same image-based algorithms used for facial recognition on social media would be applicable in manufacturing systems relevant to LLNL. Back then—and still now, fortunately—there was a lot of skepticism about how machine learning could help with science and engineering problems. Thus, I was grateful for several projects funded through the LDRD [Laboratory Directed Research and Development] program that allowed me to explore these data science pursuits.
What area of data science are you interested in learning more about?
I’m interested in foundation model(s) and how they might be applied towards the broad range of research opportunities within LLNL’s purview. In general, I am always interested in the new areas that impact data scientists, especially considering the fast pace of data science innovation, LLNL’s computing resources, and the diversity of data we encounter.
What is exciting about data science at LLNL?
What sets data science at the Lab apart from everywhere else is the scale, high consequence of error, and national/global relevance of the problems we are tackling. We have rich, sometimes sparse, but always precious datasets originating from a broad range of national security challenges. Our data scientists are key contributors in multidisciplinary teams addressing fusion, nuclear deterrence, scalable CO2 removal, bioresilience, transformative manufacturing approaches, and so much more!
What role do you see the DSI playing for the next generation of researchers, both inside and outside the Lab?
We need more data scientists, either as collaborators or staff members, so that we can deliver on our missions as the nation’s needs evolve. The DSI will continue to be a network hub for researchers and stakeholders to solve existing and future problems alike. The DSI also will facilitate partnerships between data scientists and domain experts; these relationships are key to the Lab’s Team Science approach as well as to our outside collaborations.
What are you looking forward to regarding the DSI’s future?
The Open Data Initiative (ODI) is one of the DSI’s most exciting projects. LLNL researchers generate so many interesting and unique datasets, and there’s so much technical fruit to harvest beyond the original use cases. The ODI has already reduced barriers to collaboration, and expanding its offerings will be a boon to both LLNL and wider research communities.