David Dakota Blair

David Dakota Blair is an Associate Scientist in Computer Science and Machine Learning at Brookhaven National Laboratory's Computational Science Initiative. He holds a Ph.D. in Mathematics from the CUNY Graduate Center (2015) and a B.S. in Mathematics from Texas A&M University (2006).

His research spans multiple interdisciplinary domains at the intersection of biology, data science, and national security. Blair contributes to several major projects including KBase (a collaborative platform for systems biology), Project Alexandria (enhancing nonproliferation research), SciDAC Oasis Chimbuko (real-time anomaly detection in HPC workflows), and AI Automation in the Cloud (evaluating secure AI solutions for the IAEA).

His publication record demonstrates expertise in both theoretical mathematics (particularly number theory and combinatorics) and applied computational science. Recent work shows a clear trajectory from theoretical foundations in integer partitions and combinatorics toward practical applications in systems biology, national security, and machine learning.

Blair's research interests encompass machine learning, data science, computational biology, systems biology, national security, and nonproliferation research. His work consistently bridges theoretical foundations with practical applications across diverse scientific domains.

His professional activities support data-driven discovery, scientific collaboration, and informed decision-making across multiple disciplines, with a focus on advancing science in the public interest.