Brian Gallagher is a computer scientist in LLNL’s Center for Applied Scientific Computing, where he leads the Data Science & Analytics Group. His primary research interest is developing and applying machine learning methods for scientific applications. Brian has served as a machine learning lead on numerous projects in the areas of materials discovery and optimization, nuclear threat reduction, and network science. His work contributes to multiple Strategic Deterrence, Global Security, and Physical and Life Sciences programs at LLNL. He has also served on proposal review committees, as Scientific Editor of the Computing Annual Report, as a Computing External Review Committee Technical Lead, and has provided mentorship to dozens of LLNL staff.

Brian’s research also impacts the broader data science, network science, and machine learning communities. In 2017, Brian received the IEEE Infocom Test of Time Award for his seminal work on routing messages in disruption-tolerant networks. He has served as a reviewer for dozens of journals and conferences and has served for many years on the ACM SIGKDD Conference Senior Program Committee. Brian has led more than a dozen academic collaborations, mentored over 70 graduate and undergraduate students, and currently serves as the Director of Student Programs for the LLNL Data Science Institute, where he oversees two student programs that together host 80-90 students at LLNL every summer. The Data Science Summer Institute is a highly selective 12-week summer internship program that invites graduate and undergraduate students in machine learning, applied mathematics, computer science, and statistics to work alongside an LLNL mentor on real problems in basic science and national security. The LLNL/UC Data Science Challenge is a two week educational program that provides University of California students the opportunity to gain experience working on a real-world LLNL challenge problem with LLNL staff.

For up-to-the-minute information on Brian’s publications, see his Google Scholar Profile.

• LLNL Excellence in Publication Awards: 2020 (Design Physics), 2021 (Physical & Life Sciences), and 2023 (Physical & Life Sciences).
• LLNL Spot Awards: 2019, 2020, 2023.
• IEEE International Conference on Computer Communications Test of Time Publication Award, 2017
• IEEE Data Science and Advanced Analytics Best Research Paper Honorable Mention, 2016
• IEEE International Conference on Data Mining Best Paper Award Runner Up, 2009
• ACM KDD Cup Winner, 2003