Computer scientist Brian Gallagher has always been interested in science and technology, but as his life and career have progressed, he finds, “I’m much more interested in people than I realized.” Gallagher joined LLNL’s Center for Applied Scientific Computing (CASC) in 2005 after completing his M.S. in Computer Science at UMass Amherst. Today, he works on applications of machine learning for a range of science and national security questions while also mentoring students and managing the Data Science and Analytics Group (DSAG) in CASC.

The Lab has enabled Gallagher to combine scientific pursuits with leadership positions and people-focused responsibilities. “For a long time, my primary motivation was learning new things and tackling interesting technical challenges,” he muses. “I’m still motivated by these things, but now I’m much more motivated by service to others.”

Evolving Opportunities

Throughout his career, Gallagher has seen both himself and the work evolve. “I’m working on different things with different people, and I’m playing a very different role on my projects now than I was then,” he observes.

For example, when Gallagher came to the Lab more than 15 years ago, data science was a nascent field, and its techniques were still quite new. He notes, “Data science has gone from a sort of fringe, esoteric research area to a mainstream technology being applied widely to programs across the Lab.”

Gallagher points to CASC’s participation in premier machine learning conferences—like the Conference on Neural Information Processing Systems (NeurIPS)—as evidence of this growth, stating, “It was sort of surreal to see how many of my colleagues submitted papers to NeurIPS this year. You didn’t see that five years ago, let alone ten or fifteen.”

Currently, Gallagher contributes to projects that leverage machine learning for nuclear threat-reduction applications, optimization of feedstock materials, and design of high-entropy alloys, plus a project that maps industrial control system networks and another that develops interatomic potentials. These multidisciplinary collaborations involve colleagues from Computing as well as the Global Security, Physical and Life Sciences, and Engineering directorates. “There’s no better job at the Lab than being a computer scientist because you can work on anything you want,” he asserts.

New Leadership Roles

Mentoring is very important to Gallagher, who is grateful for the advisors and opportunities that have helped pave his career path. After serving as a Data Science Challenge (DSC) mentor in 2020, Gallagher directs this year’s program for UC Merced and UC Riverside students. During the 2021 DSC, students are applying machine learning methods to time-domain optical astronomy data to detect and characterize near-Earth asteroids. The DSC is a three-week internship sponsored by LLNL’s Data Science Institute (DSI) and CASC.

Gallagher emphasizes that learning is a two-way street for students and mentors. “My main goal for the DSC is to provide an environment where everyone can grow,” he says. “There are times when the growth is palpable. You can watch the changes in people from day to day. That’s my favorite part of the experience.”

Directing the DSC has itself been a challenge. “Honestly, it’s been harder than I thought it would be,” he admits. “But I get a lot of help from my UC collaborators, [DSI administrator] Jen Bellig, [DSI director] Mike Goldman, [CASC director] Jeff Hittinger, the mentors, and the grad student team leads.”

Gallagher has also taken on a group leader position during the COVID-19 pandemic, and hasn’t yet met with his DSAG staff in person. “In addition to regularly scheduled one-on-one meetings and coffee breaks, I try to make myself visible online and stress that I’m always available to the team if anything comes up,” he states, noting that the group maximizes communication through tools like Jabber, email, and WebEx.

Ultimately, Gallagher says the group leader role is about serving others. He notes that bridging communication gaps between team members from varied backgrounds takes time and patience, but is its own reward. “It’s been very interesting to see how different people’s needs are, based on where they are in their career and where they want to be,” he explains. “Being able to provide the right opportunity to the right person at the right time and watch them grow into it is very satisfying.”