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Dr. Mark Bryden is the founding director of the Simulation, Modeling and Decision Science program at Ames Laboratory and is a professor of mechanical engineering at Iowa State University. Dr. Bryden’s research is focused on the federation of information from disparate sources (e.g., models, data, and other information elements) to create detailed models of engineered, human, and natural systems that enable engineering decision making for these complex systems. Dr. Bryden has published more than 180 peer-reviewed articles and co-authored the textbook Combustion Engineering. He has founded two successful startups based on his research work, and he has founded the nonprofit ETHOS, a community of 150+ researchers focused on meeting the needs for clean village energy in the developing world. He has received three patents, three R&D 100 awards, two Regional Excellence in Technology Transfer awards, and a National Excellence in Technology Transfer award. In 2013 he and his coauthors received the ASME Melville Medal. His professional experience includes three years as an engineer and 11 years as a manager at Westinghouse Electric in Idaho Falls, Idaho, and Pittsburgh, Pennsylvania. In addition, for more than 15 years Professor Bryden has worked on energy systems for the poor in a number of developing countries.
He received his bachelor’s degree in physics and his master’s and doctorate degrees in electrical engineering from the University of Washington. His main areas of research are distribution system analysis and power system operations. He is currently a principal research engineer at the Pacific Northwest National Laboratory for PNNL’s resilient distribution and microgrid analysis team (part of the Lab’s Electricity Infrastructure team)r. He is an adjunct faculty member at Washington State University, an affiliate assistant professor at the University of Washington, and a licensed professional engineer in Washington. He is the past chair of the Distribution System Analysis Sub-Committee and the current secretary of the Analytics Methods for Power Systems Committee (AMPS); formerly known as the Power System Analysis, Computing, and Economics (PSACE) Committee.
- Basic science: seeks to understand how nature works. This research includes experimental and theoretical work in materials science, physics, chemistry, biology, high-energy physics, and mathematics and computer science, including high performance computing.
- Applied science and engineering helps to find practical solutions to society’s problems. These programs focus primarily on energy resources, environmental management and national security.
Martin Suchara is a computational scientist at Argonne National Laboratory with expertise in quantum computing. His research focuses on quantum communication and networking, quantum error correction, quantum simulations, and optimizations of the quantum computing software stack.
Prior to joining Argonne, Martin worked at AT&T Labs and received postdoctoral training in quantum computing from UC Berkeley and the IBM T. J. Watson Research Center. Martin received his Ph.D. from the Department of Computer Science at Princeton University.
Dr. Yao is a theoretical and computational physicist, developing methods, algorithms, and codes to address condensed matter physics and materials science problems. With a degree of B.S. in department of intensive instruction in 2000 and M.S. in physics in 2003 from Nanjing University, China, he obtained his Ph.D. in physics from Iowa State University in 2009. After graduation, he took a postdoc position in Ames Laboratory. He was promoted to assistant scientist in 2011, associate scientist in 2015, and senior theoretical physicist in 2019, with an adjunct faculty position in department of Physics and Astronomy at Iowa State University. He is currently leading projects in the development of quantum computing approaches to solve ground state and dynamical properties of correlated quantum materials within the Gutzwiller quantum-classical embedding framework. He is also a key developer of the Gutzwiller density functional theory and rotationally-invariant Slave-Boson method and software.