Nick Wright
Nick Wright is the advanced technologies group lead and the NERSC chief architect. He focuses upon evaluating future technologies for potential application in scientific computing. He led the effort to optimize the architecture of the Perlmutter machine, the first NERSC platform designed to meet needs of both large scale simulation and data analysis from experimental facilities. Before moving to NERSC, he was a member of the Performance Modeling and Characterization (PMaC) group at the San Diego Supercomputing Center. He earned both his undergraduate and doctoral degrees in chemistry at the University of Durham in England.
Jim Handy
Jim Handy of Objective Analysis has over 35 years in the electronics industry including 20 years as a leading semiconductor and SSD industry analyst. Early in his career he held marketing and design positions at leading semiconductor suppliers including Intel, National Semiconductor, and Infineon. A frequent presenter at trade shows, Mr. Handy is highly respected for his technical depth, accurate forecasts, widespread industry presence and volume of publication. He has written hundreds of market reports, articles for trade journals, and white papers, and is frequently interviewed and quoted in the electronics trade press and other media.
Jean Bozman
Jean S. Bozman is an IT industry analyst focusing on cloud infrastructure and the proud founder of a new company, Cloud Architects Advisors LLC.
She has had experience as an IDC Research VP for 10+ years and has covered the semiconductor industry as an analyst for over 20 years.
Dimitri Kusnezov
Dr. Dimitri Kusnezov [Kooz-NETS-off] was confirmed as the Under Secretary for the Science and Technology Directorate (S&T) on September 8, 2022. As the science advisor to the Homeland Security Secretary, Dr. Kusnezov heads the research, development, innovation and testing and evaluation activities in support of the Department of Homeland Security’s (DHS) operational Components and first responders across the nation. S&T is responsible for identifying operational gaps, conceptualizing art-of-the-possible solutions, and delivering operational results that improve the security and resilience of the nation.
Prior to DHS, Dr. Kusnezov was a theoretical physicist working at the U.S. Department of Energy (DOE) focusing on emerging technologies. He served in numerous positions, including the Deputy Under Secretary for Artificial Intelligence (AI) & Technology where he led efforts to drive AI innovation and bring it into DOE missions, business and operations, including through the creation of a new AI Office.
Dr. Kusnezov has served in scientific and national security positions, including Senior Advisor to the Secretary of Energy, Chief Scientist for the National Nuclear Security Administration, Director of Advanced Simulation and Computing and the Director of the multi-billion-dollar National Security Science, Technology and Engineering programs. He created numerous programs, including for Minority Serving Institutions, international partners, private sector and philanthropic entities. He has worked across agencies to deliver major milestones such as DOE’s 10-year grand challenge for a 100 Teraflop supercomputer, and first of their kind and world’s fastest supercomputers.
Prior to DOE and his pursuit of public service, Dr. Kusnezov had a long career in academia where he published more than 100 articles and edited two books. He joined Yale University faculty where he was a professor for more than a decade in Theoretical Physics and served as a visiting professor at numerous universities around the world. Before this post, Dr. Kusnezov did a brief postdoc and was an instructor at Michigan State University, following a year of research at the Institut fur Kernphysik, KFA-Julich, in Germany. He earned his MS in Physics and Ph.D. in Theoretical Nuclear Physics at Princeton University and received Bachelor of Arts degrees in Physics and in Pure Mathematics with highest honors from UC Berkeley.
Dheevatsa Mudigere
Dheevatsa Mudigere is Principal Research Scientist at the AI System Co-design team at Meta. His research is mostly around on HW/SW co-design, parallel algorithms and high-performance computing. Over the past few years Dheevatsa and his team have been focusing on large scale AI, specifically deep learning recommendation models – designing and deploying efficient HW + SW solutions at FB-scale.
Øistein Jensen
Maria Thestrup
Kathryn Higgs
Sabina Ausfelt
