Stefan Wild to Lead Berkeley Lab’s Applied Mathematics and Computational Research Division
November 2, 2022
By Carol Pott
Stefan Wild, a senior computational mathematician and deputy division director of the Mathematics and Computer Science Division at Argonne National Laboratory, has been selected to serve as the next division director of Lawrence Berkeley National Laboratory’s (Berkeley Lab) Applied Mathematics and Computational Research (AMCR) Division in the Computing Sciences Area (CSA). His appointment will be effective December 1. The announcement follows an extensive international search.
“I am pleased that Wild is joining us as a leader for AMCR, a division of strategic import at the Lab and within the Computing Sciences Area,” said Lab Director Michael Witherell. “His many years of research experience, time at Argonne, and work with the DOE leaves him well suited to the role. His scientific expertise will be a welcome addition to the research enterprise here at Berkeley Lab and will continue to make a significant contribution across the DOE complex.”
Wild will be leading the AMCR Division, which conducts research and development in mathematical modeling, simulation and analysis, algorithm design, computer system architecture, and high-performance software implementation. The division collaborates directly with scientists across Berkeley Lab, the DOE, and industry to solve some of the world’s most challenging computational problems in a broad range of scientific and engineering fields, including materials science, biology, climate modeling, astrophysics, fusion science, and many others. The AMCR Division also performs research in high-performance computing technology for extreme-scale computing systems, including research into performance analysis, scientific machine learning, benchmarking, and performance engineering of scientific applications, compilers, operating systems, and runtime systems. We’re pioneering work across the quantum research ecosystem – from theory to application – partnering with industry and academia to fabricate and test quantum-based devices, develop software and algorithms, build a prototype computer and network, and apply these innovations for breakthroughs in physics and chemistry. Our products range from peer-reviewed scientific publications to scientific research codes to end-to-end computational and data analysis capabilities that enable scientists and engineers to address complex and large-scale technical challenges.
“I am delighted that Stefan Wild will soon be taking over leadership of the AMCR Division and pleased to welcome him to Berkeley Lab,” said Jonathan Carter, associate laboratory director for the Computing Sciences Area. “He is a highly respected mathematician and computational scientist with an outstanding record of research in areas of strategic importance to the division. He is also an outstanding leader, having directed major projects and managed programs of strategic importance to DOE. His combination of scientific expertise and strategic leadership makes him the ideal candidate to take on the role of AMCR Division director.”
Wild’s primary research focuses on developing model-based algorithms and software for challenging numerical optimization problems and automated learning. He has worked across scientific areas to solve difficult science and engineering problems involving advanced computer simulations, complex data, and physical experiments. At Argonne, he led a number of multidisciplinary computational science projects and shaped strategy for applied mathematics, numerical software, and statistics. Wild guides teams at Argonne and Northwestern University for diverse research efforts. He received his Ph.D. and M.S. in operations research from Cornell University and was then an Argonne Director’s Postdoctoral Fellow.
“I’m excited to join Berkeley Lab’s unique culture of team science and honored to be given the opportunity to lead the Applied Mathematics and Computational Research Division,” said Wild. “The Lab has a rich history of leadership in applied mathematics, computer science, computational science, and data science and an excellent team of researchers across its programs. The division is very well-positioned to lead major breakthroughs and drive discovery into the future, and I am looking forward to being a part of that.”
Wild is a senior fellow at Northwestern University and was also a Department of Energy Computational Science Graduate fellow. Wild is chair of the SIAM Activity Group on Computational Science and Engineering and secretary for the SIAM Activity Group on Optimization. He holds editorial responsibilities for Mathematical Programming Computation, INFORMS Journal on Computing, Data Science in Science, and the SIAM Review.
About Computing Sciences at Berkeley Lab
High performance computing plays a critical role in scientific discovery. Researchers increasingly rely on advances in computer science, mathematics, computational science, data science, and large-scale computing and networking to increase our understanding of ourselves, our planet, and our universe. Berkeley Lab’s Computing Sciences Area researches, develops, and deploys new foundations, tools, and technologies to meet these needs and to advance research across a broad range of scientific disciplines.
Founded in 1931 on the belief that the biggest scientific challenges are best addressed by teams, Lawrence Berkeley National Laboratory and its scientists have been recognized with 16 Nobel Prizes. Today, Berkeley Lab researchers develop sustainable energy and environmental solutions, create useful new materials, advance the frontiers of computing, and probe the mysteries of life, matter, and the universe. Scientists from around the world rely on the Lab’s facilities for their own discovery science. Berkeley Lab is a multiprogram national laboratory, managed by the University of California for the U.S. Department of Energy’s Office of Science.
DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.