Kennewick, Washington, United States
Demonstrated experience in building cross-institutional public-private partnerships; leading diverse scientific organizations; and building multi-disciplinary research teams in applied mathematics, data science, quantum computing, and computational biology. Nathan Baker is a Senior Director, Partnerships for Chemistry and Materials at Microsoft. Previously, Nathan was a Laboratory Fellow in the Physical and Computational Sciences Directorate at Pacific Northwest National Laboratory (PNNL) and a UW-PNNL Distinguished Faculty Fellow with the Department of Applied Mathematics at University of Washington. Other roles at PNNL have included Division Director, Business Sector Manager, Group Manager, and Initiative Lead. He was also a Visiting Professor in the Division of Applied Mathematics at Brown University as well as faculty member at Washington University in St. Louis with roles that included Associate Professor (tenured) of Biochemistry and Molecular Biophysics and Director of the Biophysics PhD program. His research interests include the development of new algorithms in applied mathematics and data science to support applications in chemistry, biology, and other domains. Current research projects include the APBS software suite (http://www.poissonboltzmann.org) which provides computational methods for modeling solvation in biomolecular systems as well as the development of new methods for uncertainty quantification. His research has been primarily funded by the US National Institutes of Health and the Department of Energy. Dr. Baker is a member of the Washington State Academy of Sciences, Fellow of the American Association for the Advancement of Science (AAAS), and a former Alfred P. Sloan Research Fellow. See https://scholar.google.com/citations?user=L9dwKyUAAAAJ&hl=en for a current publication list.
Leading an engineering team focused on application development for quantum computing.
Senior director and product manager for Azure Quantum Elements, a system designed to boost productivity for chemistry and materials R&D and accelerate scientific discovery.
This university joint appointment was concurrent with my Laboratory Fellow position at Pacific Northwest National Laboratory. Specific activities associated with this appointment included my role as Director of the NWIMPACT UW-PNNL joint institute, development of the Northwest Quantum Nexus as well as the UW-PNNL Data Science Training Program for national security.
Senior technical research staff member at PNNL. Activities included: member of leadership team for Northwest Quantum Nexus with Microsoft and University of Washington, technical leadership of data science projects for NIH and other government sponsors, as well as past leadership for PNNL's $16M internal investment in signature discovery research, including projects in machine learning, decision support, risk analysis, and signal processing with applications in bioforensics, soil microbiomes, and nuclear non-proliferation.
Lead for Division of ~100 staff with expertise in diverse computational disciplines, including computer science, data science, machine learning, graph analytics, and computational engineering. Activities in this role include: co-founder of Northwest Quantum Nexus with University of Washington and Microsoft, co-lead for development of PNNL computing strategy, advocate for increased support in several diversity activities at PNNL.
Served as point of contact between DOE ASCR and PNNL staff. Activities included leadership of a DOE Basic Research Needs workshop and report on Scientific Machine Learning.
Facilitated collaboration between Brown University and Pacific Northwest National Laboratory in mathematical approaches for multi-fidelity modeling, supported by funding from the Department of Energy Advanced Scientific Computing Research.
Led NIH- and NSF-funded research in a range of computational biophysics topics including protein metalloregulation and allostery, biomembrane structure and function, as well as biomolecular electrostatics and solvation. Directed NIH-funded research in computational methods for nanoparticle platforms for cancer diagnosis and treatment.