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Brian Adams



Brian M. Adams

BS, Mathematics, 1999
Saint Michael's College

MS, Computational Applied Mathematics, 2002
North Carolina State University

PhD, Computational Applied Mathematics, 2005
North Carolina State University

Senior Member of Technical Staff
Optimization and Uncertainty Estimation
Sandia National Laboratories

Since 2005, I have worked as a researcher in an applied mathematics and computer science research group at Sandia National Laboratories. I collaborate with incredible scientists from all disciplines and enjoy a great balance of fundamental algorithms research, software implementation, and its application to solve engineering and other science problems.

While I have always had acuity for mathematics and computer science, I decided to pursue graduate studies in applied mathematics to better understand practical uses of mathematics. A variety of coursework (e.g., modeling, numerical analysis, optimization, inverse problems, and statistics), seminars, and conferences, helped me appreciate the many possibilities. I learned that “applied mathematics” has many faces, ranging from nearly exclusively theoretical to purely practical, applying established algorithms and software to solve concrete problems. I primarily focused my research on modeling HIV infection and predicting patient outcomes (math biology). This revealed my interest in applying computational algorithms to solve problems at the intersection of disciplinary science and mathematics.

Seated in an optimization and uncertainty analysis group at SNL, I develop algorithms and interfaces to use massively parallel computing to solve design and analysis problems across the scientific disciplines. These algorithms are implemented in DAKOTA, an open-source suite of optimization, sensitivity analysis, and uncertainty quantification tools. I develop this tool in a team environment and have applied it to problems micro-electro-mechanical systems (miniature silicon-based actuators, switches, and machines) design, electrical circuit analysis, structures optimization, and molecular configuration exploration for new materials discovery. Working with end users on feature requests, bug fixes, and application consulting satiates my desire for heavy interpersonal interactions, as does the amazing team of experts with whom I work. I also leverage my PhD research experience in mathematical biology as the lead developer of a social network-based disease model characterizing disease spread (due to bioterror incident or natural outbreak) within a city's population.

My job appeals to many of my varied interests and benefits from the critical thinking and problem solving skills developed largely through my liberal arts undergraduate curriculum. The national lab environment offers a great opportunity to exercise my mathematics and computer science training in solving challenging problems in diverse areas.

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