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Appendix C Committee Biographies MARVIN L. ADAMS, Co-Chair, is the HTRI [Heat Transfer Research, Inc.] Professor of Nuclear Engineering and director of the Institute for National Security Education and Research at Texas A&M University. His research has focused on many aspects of computational science and engineering, including discretization methods, itera - tive methods, parallel algorithms, and the quantification of predictive capability. He has served as a consultant to the Lawrence Livermore National Laboratory (LLNL), Sandia National Laboratories, and Los Alamos National Laboratory and has served on a variety of review and advisory committees and panels for the laboratories, the Department of Energy, and other governmental organizations. Dr. Adams earned his B.S. (1981) from Mississippi State University followed by M.S. (1984) and Ph.D. (1986) degrees from the University of Michigan, all in nuclear engineering. From 1977 to 1982 he worked at the Tennessee Valley Authority’s Sequoyah Nuclear Plant and its support office. He joined LLNL after completing his graduate work in 1986. He left LLNL in 1992 for the faculty position that he continues to hold at Texas A&M University. In 2006 and 2007, Dr. Adams founded and directed the Center for Large-scale Scientific Simulations at Texas A&M, and from 2005 until 2009 he served as associate vice president for research. Previously Dr. Adams served on the National Research Council’s Commit - tee on Evaluation of Quantification of Margins and Uncertainties Methodology for Assessing and Certifying the Reliability of the Nuclear Stockpile. DAVID M. HIGDON, Co-Chair, is a member of the Statistical Sciences Group at the Los Alamos National Labo - ratory (LANL). He is an internationally recognized expert in Bayesian statistical modeling of environmental and physical systems. He has also led numerous programmatic efforts at LANL in the quantification of margins and uncertainties and uncertainty quantification. His recent research has focused on simulation-aided inference in which physical observations are combined with computer simulation models for prediction and inference. His research interests include space-time modeling; inverse problems in physics, hydrology, and tomography; infer- ence based on combining deterministic and stochastic models; multiscale models; parallel processing in poste - rior exploration; statistical modeling in physical, environmental, and biological sciences; and Monte-Carlo and simulation-based methods. JAMES O. BERGER is Arts and Sciences Professor of Statistics at Duke University. He was a faculty member in the Department of Statistics at Purdue University until 1997, when he moved to the Institute of Statistics and Decision Sciences (now the Department of Statistical Science) at Duke University. He has also been the director 124
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125 APPENDIX C of the national Statistical and Applied Mathematical Sciences Institute since 2002. He was the president of the Institute of Mathematical Statistics (1995-1996), chair of the Section on Bayesian Statistical Science of the Ameri - can Statistical Association (1995), and president of the International Society for Bayesian Analysis (2004). He has been involved in numerous editorial activities, including co-editorship of the Annals of Statistics (1998-2000). He has organized or participated in the organization of more than 35 conferences. Among the awards and honors that Professor Berger has received are Guggenheim and Sloan Fellowships, the COPSS [Committee of Presidents of Statistical Societies] President’s Award (1985), the Sigma Xi Research Award at Purdue University for contribution of the year to science (1993), the Fisher Lectureship (2001), election as a foreign member of the Spanish Real Academia de Ciencias (2002), election to the U.S. National Academy of Sciences (2003), an honorary doctor of science degree from Purdue University (2004), and the Wald Lectureship (2007). Professor Berger’s research has been primarily in Bayesian statistics, foundations of statistics, statistical decision theory, simulation, model selec - tion, and various interdisciplinary areas of science and industry, especially astronomy and the interface between computer modeling and statistics. He has supervised 31 Ph.D. dissertations, published more than 160 articles, and written or edited 14 books or special volumes. DEREK BINGHAM is an associate professor and the Canada Research Chair in Industrial Statistics in the Depart - ment of Statistics and Actuarial Science at Simon Fraser University. He received his Ph.D. from the Department of Mathematics and Statistics at Simon Fraser University in 1999. After graduation he joined the Department of Statistics at the University of Michigan as an assistant professor, returning to Simon Fraser in 2003. In addition, he has held a faculty affiliate position at the Los Alamos National Laboratory. The main focus of Dr. Bingham’s research is the development of statistical methodology for the design and analysis of industrial and physics experi - ments. This work focuses on developing new methodology for (1) the design and analysis of computer experiments and (2) the design and analysis of experiments in industrial problems such as optimal screening designs, response surface optimization, and optimal robust parameter designs for product variation reduction. WEI CHEN is the Wilson-Cook Chair and Professor in Engineering Design at Northwestern University. She is affiliated with the Segal Design Institute as a faculty fellow and is a professor in the Department of Mechanical Engineering, with a courtesy appointment in the Department of Industrial Engineering and Management. As a direc - tor of the Integrated Design Automation Laboratory, her current research involves issues such as simulation-based design under uncertainty, model validation, stochastic multiscale analysis and design, robust shape and topology optimization, multidisciplinary optimization, consumer choice modeling, and enterprise-driven decision-based design. She is the co-founder and director of the interdisciplinary doctoral cluster in predictive science and engi - neering design at Northwestern University, a program aiming for integrating scientific, physics-based modeling, and simulation into the design of innovative “engineered” systems. Dr. Chen is the recipient of a 1996 National Science Foundation Faculty Early Career Award and the 1998 American Society of Mechanical Engineers (ASME) Pi Tau Sigma Gold Medal achievement award. She is also a recipient of the 2005 Intelligent Optimal Design Prize and the 2006 Society of Automotive Engineering (SAE) Ralph R. Teetor Educational Award. Dr. Chen is a fellow of ASME, an associate fellow of the American Institute of Aeronautics and Astronautics, and a member of SAE. She is an elected member of the ASME Design Engineering Division Executive Committee and an elected Advi - sory Board member of the Design Society, an international design research community. She is an associate editor of the ASME Journal of Mechanical Design and serves as the review editor of Structural and Multidisciplinary Optimization. In the past, she served as the chair and a member of the ASME Design Automation Executive Com - mittee (2002-2007) and was an associate editor of the Journal of Engineering Optimization. ROGER GHANEM is the Gordon S. Marshall Professor of Engineering Technology in the Viterbi School at the University of Southern California (USC). Dr. Ghanem has a Ph.D. in civil engineering from Rice University and had served on the faculty of the Schools of Engineering at SUNY [State University of New York]-Buffalo and Johns Hopkins University before joining USC in 2005. Dr. Ghanem’s research is mainly in the area of computational sci - ence and engineering with a focus on uncertainty quantification and prediction validation in complex systems. His recent interests include the sustainability of coupled interacting systems such as the SmartGrid and the interface of
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126 ASSESSING THE RELIABILITY OF COMPLEX MODELS human and natural environments, as well as the predictability of physical behaviors exhibiting coupling between multiple underlying phenomena and scales. Dr. Ghanem has more than 100 refereed journal publications in the general areas of stochastic modeling and computations and dynamical systems. He has received several awards for his teaching and research, is the founding editor of Lecture Notes in Mechanics (Engineering Mechanics Insti- tute of the American Society of Civil Engineers [ASCE-EMI]), and serves on the advisory board of a number of professional journals. He currently serves on the Board of Governors of the ASCE-EMI, is program director of the Society of Industrial and Applied Mathematics (SIAM) Activity Group on Uncertainty Quantification (SIAG/ UQ), and chairs the U.S. Association for Computational Mechanics committee of SIAG/UQ. OMAR GHATTAS is the John A. and Katherine G. Jackson Chair in Computational Geosciences and a profes - sor of geological sciences and mechanical engineering at the University of Texas at Austin. He is also a research professor in the Institute for Geophysics, director of the Center for Computational Geosciences in the Institute for Computational Engineering and Sciences, professor of biomedical engineering and computer sciences (by cour- tesy), co-chief applications scientist for the 580 Teraflops NSF Track 2 supercomputer at the Texas Advanced Com - puting Center, and director of the KAUST-UT [King Abdullah University of Science and Technology– University of Texas at Austin] Academic Excellence Alliance. From 1989 to 2005, he was a professor at Carnegie Mellon University. He has been a visiting professor at the Institute for Computer Applications in Science and Engineer - ing at NASA-Langley Research Center, the Center for Applied Scientific Computing at the Lawrence Livermore National Laboratory, and the Computer Science Research Institute at the Sandia National Laboratories. Professor Ghattas’s research interests are in the forward and inverse modeling and the optimal design and control of complex systems in the geological, mechanical, and biomedical engineering sciences, with particular emphasis on large- scale simulation on parallel supercomputers. He received the 1998 Allen Newell Medal for Research Excellence, the Supercomputing 2002 Best Technical Paper Award, the 2003 Gordon Bell Prize for Special Accomplishment in Supercomputing, the 2004/2005 CMU College of Engineering Outstanding Research Prize, the SC2006 HPC [High Performance Computing] Analytics Challenge Award, and the TeraGrid 2008 Capability Computing Chal - lenge Award, and he was a finalist for the 2008 Gordon Bell Prize. Professor Ghattas’s recent professional activities have included service in the following capacities: he has organized 10 conferences and workshops in computational science and engineering; delivered 15 keynote or plenary talks at major international conferences; was program director for the Computational Science and Engineering Activity Group of the Society for Industrial and Applied Mathematics (SIAM); served as founding editor-in-chief of SIAM’s Computational Science and Engineering series; was associate editor of the SIAM Journal on Scientific Computing and an editorial board member of seven other journals; served as a member of the SIAM Program Committee; and was a member of the Science Steering Committee for the Computational Infrastructure for Geodynamics project. JUAN MEZA is dean of the School of Natural Sciences at the University of California, Merced. Prior to joining the University of California, Merced, he was the department head of High Performance Computing Research at the Lawrence Berkeley National Laboratory, where he oversaw work in computational science and mathematics, computer science and future technologies, scientific data management, visualization, and numerical algorithms and application development. His current research interests include nonlinear optimization with an emphasis on methods for parallel computing. He has also worked on various scientific and engineering applications including scalable methods for nanoscience, electric power grid reliability, cyber security, molecular conformation prob - lems, optimal design of chemical vapor deposition furnaces, and semiconductor device modeling. Dr. Meza also held the position of Distinguished Member of the Technical Staff at the Sandia National Laboratories and served as the manager of the Computational Sciences and Mathematics Research Department. In this capacity, he acted as the Research Foundation Network Research program manager and the ASCI Problem Solving Environment Advanced Software Development Environment program manager, and he served as a member of the Sandia/ California Research Council. Dr. Meza was recently named to the Top 100 Influentials list of Hispanic Business Magazine in the area of science. In addition, he was elected a fellow of the American Association for the Advance - ment of Science. In 2008, Dr. Meza was the recipient of the Blackwell-Tapia Prize and the SACNAS [Society for the Advancement of Chicanos and Native Americans in Science] Distinguished Scientist Award. He was also a
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127 APPENDIX C member of the team that won the 2008 ACM Gordon Bell Award for Algorithm Innovation. Dr. Meza has served on numerous external committees, including the National Science Foundation’s Mathematical and Physical Sci - ences Advisory Committee, the Department of Energy’s Advanced Scientific Computing Advisory Committee, the Mathematical Sciences Research Institute’s Human Resources Advisory Committee, the Board of Trustees of the Institute for Pure and Applied Mathematics, the Board of Governors of the Institute for Mathematics and Its Applications, and the Board of Trustees of the Society of Industrial and Applied Mathematics. ERIC MICHIELSSEN is a professor of electrical and computer engineering at the University of Illinois at Urbana-Champaign (UIUC). His research interests include all aspects of theoretical and applied computational electromagnetics with an emphasis on the development of fast frequency and time domain integral-equation-based techniques for analyzing electromagnetic phenomena and robust optimizers for electromagnetic/optical devices. Professor Michielssen is the (co-)author of 120 journal articles and book chapters and 180 conference papers and abstracts. He was the recipient of a 1994 International Union of Radio Scientists (URSI) Young Scientist Fellow - ship, a 1995 National Science Foundation CAREER Award, and the 1998 Applied Computational Electromagnetics Society Valued Service Award. In addition, he was named the 1999 URSI United States National Committee Henry G. Booker Fellow and was selected as the recipient of the 1999 URSI Koga Gold Medal. Recently, he was awarded the UIUC’s 2001 Xerox Award for Faculty Research and was appointed a Beckman Fellow in its Center for Advanced Studies, a UIUC Scholar, and a Sony Faculty Fellow. He is an associate editor for IEEE Transac- tions on Antennas and Propagation and a fellow of the Institute of Electrical and Electronics Engineers (IEEE). VIJAYAN N. NAIR is the Donald A. Darling Professor of Statistics and a professor of industrial and operations engineering at the University of Michigan. He was chair of the Department of Statistics from 1998 to 2010. His past experience includes 15 years as a research scientist at Bell Laboratories. He has a broad range of interests in statistical methodology and applications, especially in engineering statistics. He is involved with the Center for Radiative Shock Hydrodynamics (CRASH) at the University of Michigan, one of five national centers funded under the Predictive Science Academic Alliance Program by the National Nuclear Security Administration’s Office of Advanced Simulation and Computing. As part of this center, Dr. Nair has been involved in modeling and analyzing data from large-scale simulation models and in uncertainty quantification. He is the president-elect of the International Statistical Institute and president of the International Society for Business and Industrial Sta - tistics. He is a senior fellow of the Michigan Society of Fellows and a fellow of the American Association for the Advancement of Science, the American Society for Quality, the American Statistical Association, and the Institute of Mathematical Statistics. He currently serves on the National Research Council’s Board on Mathematical Sci - ences and Their Application, is chairing or has (co)chaired three committees, and has served on many others. He has a Ph.D. in statistics from the University of California, Berkeley. CHARLES W. NAKHLEH manages the Inertial Confinement Fusion Target Design Department in the Pulsed Power Sciences Center at the Sandia National Laboratories. He supervises theoretical design and analysis efforts for inertial confinement fusion (ICF) targets for the Z pulsed-power facility. His department is also involved in the analysis and design of experiments for the National Ignition Campaign. Dr. Nakleh joined Sandia National Laboratories in December 2007. From 2005 to 2007, he was the group leader (acting) and deputy group leader of the Thermonuclear Applications Group (X-2) at the Los Alamos National Laboratory (LANL), where, among other tasks, he oversaw the W88 and Reliable Replacement Warhead efforts. He had spent nearly a decade before that as a staff member in X-2, working on a wide variety of weapons-physics and design issues, including the develop - ment and application of the quantification of margins and uncertainties (QMU) methodology to simulation-based predictions. Dr. Nakleh is a graduate of the Theoretical Institute of Thermonuclear and Nuclear Studies (TITANS) program at LANL. He was a member of study teams that received Department of Energy Awards of Excellence in 1999, 2000, 2005, and 2007. He has served on a wide variety of advisory panels, including as a founding member of the National Nuclear Security Administration’s (NNSA’s) Predictive Science Panel, the LANL director’s advisory panel on weapons certification, a consultant to the 2009 JASON study on warhead Life Extension Programs, an adviser to the Undersecretary of Energy for Science on the National Ignition Campaign, and an adviser to NNSA
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128 ASSESSING THE RELIABILITY OF COMPLEX MODELS on a variety of weapons physics issues. His research interests span a wide range of ICF, radiation effects, and other applications of high energy density physics, and applications of Bayesian inference techniques. He received his Ph.D. in physics from Cornell University in 1996. DOUGLAS NYCHKA is the director of the Institute of Mathematics Applied to Geosciences at the National Center for Atmospheric Research (NCAR), an interdisciplinary component with a focus on transferring innovative mathematical and statistical tools to the geosciences. Dr. Nychka is a statistical scientist with an interest in the problems posed by the analysis of geophysical data sets. He received his Ph.D. from the University of Wisconsin in 1983. Subsequently he spent 14 years as a faculty member at North Carolina State University. His interest in environmental problems and a background in fitting curves and surface to spatial data led him to assume leader - ship of the statistics project at NCAR. STEPHEN M. POLLOCK was the Herrick Professor of Manufacturing and a professor of industrial and opera - tions engineering at the University of Michigan until his recent retirement. He taught courses in decision analysis, mathematical modeling, dynamic programming, and stochastic processes. His research activities include develop - ing cost-optimal monitoring and maintenance policies, sequential hypothesis testing, modeling large multiserver systems, and dynamic optimization of radiation treatment plans. He was the director of the Program in Financial Engineering and the Engineering Global Leadership honors program. He has been an area editor of Operations Research, senior editor of IIE Transactions, president (1986) of the Operations Research Society of America, and a senior fellow of the University of Michigan Society of Fellows. Dr. Pollock is a founding fellow of the Institute for Operations Research and the Management Sciences; he was awarded its Kimball Medal in 2002. He was a member of the Army Science Board and is a member of the National Academy of Engineering. His previous National Research Council experience includes chairing the Committee on National Statistics’ (CNSTAT’s) Panel on Operational Test Design and Evaluation of the Interim Armored Vehicle (2002-2003), serving on the Com - mittee on Applied and Theoretical Statistics (CATS) and on CNSTAT’s Panel on Statistical Methods for Testing and Evaluating Defense Systems (1995-1998), and serving on the Committee on Modeling and Simulation for Defense Transformation and on the Committee on Methodological Improvements to the Department of Homeland Security’s Biological Agent Risk Analysis. HOWARD A. STONE is a professor in the Department of Mechanical and Aerospace Engineering at Princeton University. He received the B.S. degree in chemical engineering from the University of California at Davis in 1982 and his Ph.D. in chemical engineering from the California Institute of Technology in 1988. Following a postdoctoral year in the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge, in 1989 he joined the faculty of the (now) School of Engineering and Applied Sciences at Harvard University, where he eventually became the Vicky Joseph Professor of Engineering and Applied Mathematics. In 1994 he received both the Joseph R. Levenson Memorial Award and the Phi Beta Kappa Teaching Prize, which are the only two teaching awards given to faculty in Harvard College. In 2000 he was named a Harvard College Professor for his contribu - tions to undergraduate education. Recently he moved to Princeton University where he is the Donald R. Dixon ’69 and Elizabeth W. Dixon Professor in the Department of Mechanical and Aerospace Engineering. Professor Stone’s research interests are in fluid dynamics, especially as it arises in research and applications at the interfaces of engineering, chemistry, and physics. His group tackles problems with a combination of experimental, theoreti - cal, and modeling approaches. He has received the National Science Foundation Presidential Young Investigator Award, is a fellow of the American Physical Society (APS), and is past chair of the Division of Fluid Dynamics of the APS. For 10 years he served as an associate editor of the Journal of Fluid Mechanics, and he is currently on the editorial or advisory boards of the New Journal of Physics, Soft Matter and Physics of Fluids. He is the first recipient of the G.K. Batchelor Prize in Fluid Dynamics, which was awarded in August 2008. In 2009 he was elected to the National Academy of Engineering. ALYSON G. WILSON is a research staff member at the Institute for Defense Analyses (IDA) Science and Tech - nology Policy Institute. Before coming to IDA, she was an associate professor in the Department of Statistics
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129 APPENDIX C at Iowa State University. Dr. Wilson received her Ph.D. in statistics from Duke University, her M.S. in statistics from Carnegie Mellon University, and her B.A. in mathematical sciences from Rice University. She is a fellow of the American Statistical Association and a recognized expert in statistical reliability, Bayesian methods, and the application of statistics to problems in defense and national security. Prior to joining Iowa State University, Dr. Wilson was a project leader and technical lead for Department of Defense programs in the Statistical Sciences Group at the Los Alamos National Laboratory (1999-2008), a senior statistician and operations research analyst with Cowboy Programming Resources (1995-1999), and a mathematical statistician at the National Institutes of Health (1991-1992). She is a founder and past-chair of the American Statistical Association’s Section on Statistics in Defense and National Security. She is a member of the Technometrics management committee and serves as reviews editor for the American Statistician and the Journal of the American Statistical Association. In addition to numerous publications, Dr. Wilson has co-authored a book, Bayesian Reliability, and has co-edited two other books, Statistical Methods in Counterterrorism: Game Theory, Modeling, Syndromic Surveillance, and Biometric Authentication and Modern Statistical and Mathematical Methods in Reliability. She holds a patent for her early work in medical imaging. MICHAEL R. ZIKA is a project leader and an associate division leader in the AX Division at the Lawrence Livermore National Laboratory (LLNL). He earned both his B.S. (1991) and his M.S. (1992) from Purdue Uni- versity, and his Ph.D. (1997) from Texas A&M University, all in nuclear engineering. In 1997 he joined LLNL as a computational physicist. His work focused on algorithms and physics models for modeling radiative transfer. As a project leader, Dr. Zika has led a large team of computational physicists and computer scientists to deliver mas - sively parallel two-dimensional/three-dimensional multi-physics simulation tools for high energy density physics in support of the Stockpile Stewardship Program. These tools have been used to design and analyze experiments on the National Ignition Facility. In 2006 he led a team and in 2009 was a member of a team that received a Department of Energy Award of Excellence. Dr. Zika has served as an adjunct faculty member at Texas A&M University and as a visiting faculty member at the University of California, Berkeley. He has participated in a variety of strategic planning efforts at the request of the Advanced Simulation and Computing Program Office in the Department of Energy’s National Nuclear Security Administration.