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Proceedings of a Workshop on Statistics on Networks Appendix B Biographical Sketches of Workshop Speakers Stephen P. Borgatti, Boston College, received his Ph.D. in mathematical social science from the University of California, Irvine, in 1989. His research interests are in shared cognition and social networks. He is the author of ANTHROPAC, a software package for cultural domain analysis, and UCINET, a software package for social network analysis. He is a past director of the National Science Foundation’s Summer Institute for Research Methods, as well as a past president of the International Network for Social Network Analysis, the professional association for social network researchers. He currently serves as associate editor for a number of journals, including Field Methods and Computational and Mathematical Organizational Theory, and is senior editor for Organization Science. He is currently professor and chair of the Organization Studies Department at the Carroll School of Management at Boston College. Kathleen M. Carley, Carnegie Mellon University, received her Ph.D. from Harvard University in mathematical sociology. She is currently a professor of computer science at Carnegie Mellon University. She also directs the center for Computational Analysis of Social and Organizational Systems (CASOS). CASOS is a university-wide center for understanding complex systems through the combined application of computer science, social science, and social networks. Her research combines cognitive science, social networks, and computer science to address complex social and organizational problems. Her specific research areas are computational social and organization theory; group, organizational, and social adaptation and evolution; social and dynamic network analysis; computational text analysis; and the impact of telecommunication technologies and policy on communication, information diffusion, and disease contagion and response within and among groups, particularly in disaster or crisis situations. Her models meld multiagent technology with network dynamics and empirical data. Jean M. Carlson, University of California, Santa Barbara, received a B.S.E. in electrical engineering and computer science from Princeton University in 1984, an M.S.E. in applied and engineering physics from Cornell University in 1987, and a Ph.D. in theoretical condensed matter physics from Cornell in 1988. After postdoctoral work at the Institute for Theoretical Physics at the University of California, Santa Barbara (UCSB), she joined the faculty at UCSB in 1990, where she is currently a professor of physics. She is a recipient of fellowship awards from the Sloan Foundation, the David and Lucile Packard Foundation, and the McDonnell Foundation. Dr. Carlson's research interests include a combination of foundational work and a variety of practical applications of complex-systems theory, including earthquakes, wildfires, and optimization and design in networks. Mingzhou Ding, University of Florida, received his B.S. in astrophysics from Peking University in 1982 and his Ph.D. in physics from the University of Maryland in 1990. He is currently a professor in the Department of Biomedical Engineering at the University of Florida. His main research interest includes cognitive neuroscience and related signal processing problems. John Doyle, California Institute of Technology, is the John G. Braun Professor of Control and Dynamical Systems, Electrical Engineer, and BioEngineering at Caltech. He has B.S. and M.S. degrees in electrical engineering from the Massachusetts Institute of Technology (1977) and a
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Proceedings of a Workshop on Statistics on Networks Ph.D. in mathematics from the University of California, Berkeley (1984). His early work was in the mathematics of robust control, LQG robustness, (structured) singular value analysis, H-infinity, and there have been many recent extensions. He coauthored several books and software toolboxes currently used at over 1,000 sites worldwide, the main control analysis tool for high-performance commercial and military aerospace systems, as well as many other industrial systems. Early examples of industrial applications of his work include various airplanes—X-29, F-16XL, F-15 SMTP, B-1, B-2, 757; Shuttle Orbiter; electric power generation; distillation; catalytic reactors; backhoe slope-finishing; active suspension; and CD players. His current research interests are in theoretical foundations for complex networks in engineering and biology, as well as multiscale physics. His group led the development of the open source Systems Biology Markup Language (SBML) and the Systems Biology Workbench (SBW), which have become the central software infrastructures for systems biology (www.sbml.org), and also released the analysis toolbox SOSTOOLS (www.cds.caltech.edu/sostools). He was the theoretical lead on the team that developed the FAST protocol and shattered multiple world land speed records (netlab.caltech.edu). His prize papers include the Institute of Electrical and Electronics Engineers (IEEE) Baker Award (for the top research paper in all of the IEEE’s approximately 90 journals, also ranked in the top 10 “most important” papers worldwide in pure and applied mathematics from 1981-1993), the IEEE Automatic Control Transactions Axelby Award (twice), and the American Automatic Control Council (AACC) Schuck Award. Individual awards that he has received include the IEEE Control Systems Field Award (2004) and the Centennial Outstanding Young Engineer (1984). He has held national and world records and championships in various sports. Deborah Estrin, University of California at Los Angeles, holds a Ph.D. in Electrical Engineering and Computer Science (EECS) from MIT (1985) and a B.S. in EECS from the University of California at Berkeley (1980) and is a professor of computer science at the University of California at Los Angeles, where she holds the Jon Postel Chair in Computer Networks and is the founding director of the National Science Foundation Science and Technology Center for Embedded Networked Sensing (CENS). Dr. Estrin has been instrumental in defining the research agenda for wireless sensor networks. Her research focuses on technical challenges posed by autonomous, distributed, physically coupled systems. She is particularly interested in environmental monitoring applications and is on the National Ecological Observatory Network (NEON) design team. Earlier in her career she contributed to the design of Internet routing protocols. Dr. Estrin is a member of the NSF Computer and Information Sciences and Engineering (CISE) Advisory Committee and of the National Research Council’s (NRC’s) Computer Science and Technology Board. Mark S. Handcock, University of Washington, is a professor of statistics and sociology, Department of Statistics, University of Washington, Seattle. His work focuses on the development of statistical models for the analysis of social network data, spatial processes, and demography. He received his B.Sc. from the University of Western Australia and his Ph.D. from the University of Chicago. Descriptions of his work are available at http://www.stat.washington.edu/handcock. Nicho Hatsopoulos, University of Chicago, received his B.A. in physics in 1984 from Williams College. He received a master’s (Sc.M.) in psychology in 1991 and a Ph.D. in cognitive science in 1992, both from Brown University. He was a postdoctoral fellow at the California Institute of Technology from 1992 to1995 and then again at Brown University from 1995 to 1998. From 1998 to 2001, he was an assistant professor of research in the Department of Neuroscience at Brown University. From 2002 to the present, he has been an assistant professor in the
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Proceedings of a Workshop on Statistics on Networks Department of Organismal Biology and Anatomy and on the Committees of Computational Neuroscience and Neurobiology at the University of Chicago. Peter Hoff, University of Washington, is an assistant professor in the Departments of Statistics and Biostatistics, and a member of the Center for Statistics and the Social Sciences at the University of Washington in Seattle. Ravi Iyengar, Mount Sinai School of Medicine, is the Rosenstiel Professor and Chair of the Department of Pharmacology and Biological Chemistry at Mount Sinai School of Medicine, New York, N.Y. Trained as a biochemist, Dr. Iyengar has used biochemical and molecular biological approaches to study cell signaling, with a focus on heterotrimeric G protein pathways. Over the past decade, the Iyengar laboratory has also used computational approaches to understand the regulatory capabilities of cellular signaling networks. The laboratory’s most recent studies using graph theory approaches were published in Science in August 2005. David Jensen, University of Massachusetts, Amherst, is an associate professor of computer science and director of the Knowledge Discover Laboratory at the University of Massachusetts. He received a doctor of science in engineering at Washington University in 1991. His research interests are knowledge discovery in relational data, social network analysis, and evaluation, social impacts, and government applications of knowledge discover systems. Jon Kleinberg, Cornell University, received his Ph.D. in computer science from MIT in 1996; he subsequently spent a year as a visiting scientist at the IBM Almaden Research Center and is now a professor in the Department of Computer Science at Cornell University. His research interests are centered on issues at the interface of networks and information, with an emphasis on the social and information networks that underpin the Web and other online media. He is the recipient of an NSF Career Award, an Office of Naval Research Young Investigator Award, an Alfred P. Sloan Foundation Fellowship, a David and Lucile Packard Foundation Fellowship, teaching awards from the Cornell Engineering College and Computer Science Department, and the 2001 National Academy of Sciences Award for Initiatives in Research. David Kleinfeld, University of California, San Diego, who now lives in La Jolla, is part of a generation of scientists who trained in physics in the 1980s and 1990s and now devote themselves to problems in the neurosciences. Dr. Kleinfeld focuses on feedback control in somatosensation, using the rat vibrissa sensorimotor system as a model, and on blood flow dynamics in vascular loops, using rodent neocortex as a model system. Aspects of the later work involve the use of nonlinear optics as a tool to measure and perturb flow. Dr. Kleinfeld takes particular pride in the advanced education of graduate and postdoctoral students through his involvement in summer programs on computational modeling, data analysis, and imaging held at Woods Hole and at Cold Spring Harbor. Eric Kolaczyk, Boston University, is associate professor of statistics and director of the Program in Statistics in Boston University’s Department of Mathematics and Statistics and a member of the Center for Information and Systems Engineering (CISE) at the university. His research focuses on the statistical modeling and analysis of various types of temporal, spatial, and network data, with a particular emphasis on the use of sparseness in inference. His work has resulted in new methods for signal and image denoising, tomographic image reconstruction, disease mapping, high-level image analysis in land cover classification, and analysis of computer network measurements. Professor Kolaczyk's publications have appeared in the literatures on statistical theory and methods, engineering, astronomy, geography, and computer science. His
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Proceedings of a Workshop on Statistics on Networks work has been supported by various grants from the National Science Foundation and the Office of Naval Research. Nancy Kopell, Boston University, has a Ph.D. in mathematics and has been working in neuroscience for about 20 years. Her mathematical focus is dynamical systems, especially geometrical theory of systems with multiple time scales. Scientifically, she has worked on a range of questions including pattern formation in chemical systems and central pattern generators for locomotion. She is currently focusing on how the nervous system makes use of its dynamics, especially its rhythmic dynamics, to help with sensory processing, cognition, and motor preparation. Eve Marder, Brandeis University, is the Victor and Gwendolyn Beinfield Professor of Neuroscience in the Biology Department and Volen Center for Complex Systems at Brandeis University. She received her Ph.D. in 1974 from the University of California, San Diego, and subsequently conducted a 1-year postdoctoral at the University of Oregon and then a 3-year postdoctoral at the Ecole Normale Superieure in Paris, France. She became an assistant professor in the Biology Department at Brandeis University in 1978 and was promoted to professor in 1990. During her time at Brandeis University, Professor Marder has been instrumental in the establishment of both undergraduate and graduate programs in neuroscience. Professor Marder has served on the editorial board of the Journal of Neurophysiology since 1989. For almost 6 years she was a reviewing editor for the Journal of Neuroscience. Additionally, she now sits on the editorial boards of Physiological Reviews, Journal of Neurobiology, Journal of Comparative Neurology, Current Biology, Current Opinion in Neurobiology, Journal of Experimental Biology, and Journal of Comparative Physiology. She has served on numerous study sections and review panels for the National Institutes of Health, NSF, and other funding agencies. She also has served on the Council for the Society for Neuroscience, Council of the Biophysical Society, and several American Phytopathological Society (APS) committees. Professor Marder is a fellow of the American Association for the Advancement of Science, a fellow of the American Academy of Arts and Sciences, a trustee of the Grass Foundation, and a member of the National Academy of Sciences. She was the Forbes Lecturer at the Marine Biological Laboratory (MBL) in 2000 and the Einer Hille Lecturer at the University of Washington in 2002. She has studied the dynamics of small neuronal networks using the crustacean stomatogastric nervous system. Her work was instrumental in demonstrating that neuronal circuits are not “hard-wired” but can be reconfigured by neuromodulatory neurons and substances to produce a variety of outputs. Together with Larry Abbott, her laboratory pioneered the “dynamic clamp.” She was one of the first experimentalists to forge long-standing collaborations with theorists and has for almost 15 years of combined experimental work with insights from modeling and theoretical studies. Her work today focuses on understanding how stability in networks arises despite ongoing channel and receptor turnover and modulation, both in developing and adult animals. Martina Morris, University of Washington, received a B.A. in sociology from Reed College in 1980, an M.A. in statistics from the University of Chicago in 1986, and a Ph.D. in sociology from the University of Chicago in 1989. She is the director of the Center for Studies in Demography and Ecology and holds the Blumstein-Jordan Chair in the Department of Sociology at the University of Washington. Her research is interdisciplinary, intersecting with demography, economics, epidemiology and public health, and statistics.
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Proceedings of a Workshop on Statistics on Networks Mark Newman, University of Michigan, received his Ph.D. in theoretical physics from the University of Oxford in 1991 and worked at Cornell University and the Santa Fe Institute before moving to the University of Michigan in 2002. He is currently associate professor of physics and complex systems at the University of Michigan and a member of the external faculty of the Santa Fe Institute. He has research interest in network statistics and modeling, epidemiology, computer algorithms, and cartography.
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