Annual Applied Complexity Network and Board of Trustees Symposium: New Complexity Economics Speakers
From Santa Fe Institute Events Wiki
November 8 - 9, 2019
Santa Fe Institute
W. Brian Arthur is an External Professor at the Santa Fe Institute, and Visiting Researcher in the Systems Sciences Lab at PARC (formerly Xerox Parc) in Palo Alto. Arthur pioneered the modern study of positive feedbacks or increasing returns in the economy--in particular their role in magnifying small, random events in the economy and locking in dominant players. This work has gone on to become the basis of our understanding of the high-tech economy. In 2009 he published the book "The Nature of Technology: What it Is and How it Evolves", an elegant and powerful theory of technology's origins and evolution.
Arthur is also one of the pioneers of the science of complexity. His association with the Santa Fe Institute goes back to 1987. He is a member of SFI's Founders Society, and in 1988 directed its first research program—work that has subsequently become the basis for Complexity Economics. He has served many years on SFI's Science Board and Board of Trustees. From 1983 to 1996 Arthur was Morrison Professor of Economics and Population Studies at Stanford University, at the time of appointment the youngest endowed professor at Stanford.
Brian Arthur is the recipient of the Schumpeter Prize in economics, the Lagrange Prize in complexity science, and two honorary doctorates. He earned his Ph.D. from Berkeley in Operations Research and has other degrees in economics, electrical engineering, and mathematics.
Rob Axtell is a Professor at George Mason University and External Professor at Santa Fe Institute. He works at the intersection of economics, behavioral game theory, and multi-agent systems computer science. His most recent research attempts to emerge a macroeconomy from tens of millions of interacting agents. He is Department Chair of the new Department of Computational Social Science at George Mason University (Fairfax, Virginia, USA). He teaches courses on agent-based modeling, mathematical modeling, and game theory. His research has been published in "Science," "Proceedings of the National Academy of Sciences USA," and leading field journals. Popular accounts have appeared in newspapers, magazines, books, online, on the radio and in museums. His is the developer of Sugarscape, an early attempt to do social science with multi-agent systems, andco-author of "Growing Artificial Societies: Social Science from the Bottom Up" (MIT Press 1996). Previously, he was a Senior Fellow at the Brookings Institution (Washington, D.C. USA) and a founding member of the Center on Social and Economic Dynamics there. He holds an interdisciplinary Ph.D. from Carnegie Mellon University (Pittsburgh, USA).
Eric Beinhocker is a Professor of Public Policy Practice at the Blavatnik School of Government, University of Oxford and External Professor at Santa Fe Institute. He is also the Executive Director of the Institute for New Economic Thinking at the University’s Oxford Martin School. INET Oxford is a research center devoted to applying leading-edge interdisciplinary approaches to economic theory and public policy practice. INET Oxford researchers are working on issues ranging from financial system stability, to innovation and growth, economic inequality, and environmental sustainability. Beinhocker is also a Supernumerary Fellow in Economics at Oriel College, an External Professor at the Santa Fe Institute, and a Visiting Professor of Economics and Public Policy at Central European University in Budapest.
Joshua Epstein is Professor of Epidemiology at the New York University College of Global Public Health and External Professor at Santa Fe Institute. A pioneer in agent-based computational modeling, Epstein has recently done groundbreaking work on epidemics and bioterrorism. He has published widely in the modeling area, including articles on the dynamics of civil violence, the demography of the Anasazi, the evolution of norms, and the epidemiology of smallpox and pandemic flu.
Epstein also serves as a member of the New York Academy of Sciences and is a former Senior Fellow in Economics and Director of the center of Social and Economic Dynamics at the Brookings Institution. He is a recipient of the prestigious 2008 NIH Director’s Pioneer Award, lead investigator in Modeling and Simulation for the DHS University Center of Excellence on Preparedness and Catastrophic Event Response (PACER) at the Johns Hopkins School of Medicine, and director of Global Epidemic Modeling for the National Institutes of Health's Models of Infectious Disease Agent Study (MIDAS), a collaboration of research and informatics groups to develop computational models of infectious agents and control strategies.
J. Doyne Farmer is the Director of the Complexity Economics programme at the Institute for New Economic Thinking at the Oxford Martin School, Professor in the Mathematical Institute at the University of Oxford, and External Professor at Santa Fe Institute. He has broad interests in complex systems, and has done research in dynamical systems theory, time series analysis and theoretical biology. At present his main interest is in developing quantitative theories for social evolution, in particular for financial markets (which provide an accurate record of decision making in a complex environment) and the evolution of new technologies (whose performance through time provides a quantitative record of human achievement). He was a founder of Prediction Company, a quantitative trading firm that was recently sold to the United Bank of Switzerland, and was their chief scientist from 1991 - 1999. During the eighties he worked at Los Alamos National Laboratory, where he was an Oppenheimer Fellow, founding the Complex Systems Group in the theoretical division. He began his career as part of the U.C. Santa Cruz Dynamical Systems Collective, a group of physics graduate students who did early research in what later came to be called "chaos theory". In his spare time during graduate school he led a group that designed and built the first wearable digital computers (which were used to beat the game of roulette). For popular press see The Newtonian Casino by Thomas Bass, Chaos by Jim Gleick, Complexity by Mitch Waldrup, and The Predictors by Thomas Bass.
Jessica Flack is a Professor at SFI where she runs the Collective Computation Group. They work on fundamental problems in evolutionary theory concerning collective behavior, collective computation, and collective intelligence—at all levels of biological organization—from societies of cells to societies of individuals to machine-human hybrid societies. Her particular interests are in the role of collective computation/intelligence in the origin of space and time scales and in the emergence of robust structure and function in nature and society. She is fascinated with the idea that components in adaptive systems construct their macroscopic worlds through collective coarse-graining in evolutionary and/or learning time.
Matthew Jackson is the William D. Eberle Professor of Economics at Stanford University, External Professor at Santa Fe Institute where he is on the Science Board, and a senior fellow of CIFAR. He was at Northwestern University and Caltech before joining Stanford, and received his BA from Princeton University in 1984 and PhD from Stanford in 1988. Jackson's research interests include game theory, microeconomic theory, and the study of social and economic networks, on which he has published many articles and the books The Human Network and Social and Economic Networks. He also teaches an online course on networks and co-teaches two others on game theory. Jackson is a Member of the National Academy of Sciences, a Fellow of the American Academy of Arts and Sciences, a Fellow of the Econometric Society, a Game Theory Society Fellow, and an Economic Theory Fellow, and his other honors include the von Neumann Award, a Guggenheim Fellowship, the Social Choice and Welfare Prize, the B.E.Press Arrow Prize for Senior Economists, and teaching awards.
David Krakauer is the President and William H. Miller Professor of Complex Systems at the Santa Fe Institute. His research explores the evolution of intelligence on earth. This includes studying the evolution of genetic, neural, linguistic, social and cultural mechanisms supporting memory and information processing, and exploring their shared properties. He served as the founding Director of the Wisconsin Institute for Discovery, the Co-Director of the Center for Complexity and Collective Computation, and Professor of mathematical genetics all at the University of Wisconsin, Madison. David has been a visiting fellow at the Genomics Frontiers Institute at the University of Pennsylvania, a Sage Fellow at the Sage Center for the Study of the Mind at the University of Santa Barbara, a long-term Fellow of the Institute for Advanced Study in Princeton, and visiting Professor of Evolution at Princeton University. In 2012 Dr. Krakauer was included in the Wired Magazine Smart List as one of 50 people "who will change the World.” In 2016 Krakauer was included in Entrepreneur Magazine’s visionary Leaders advancing global research and business.
Blake LeBaron is the Abram L. and Thelma Sachar Chair of International Economics at the International Business School, Brandeis University. LeBaron was at the University of Wisconsin from 1988-1998, and also served as director of the Economics Program at the Santa Fe Institute in 1993. He was a Sloan Fellow, and is a recent recipient of the Market Technicians Association Mike Epstein award. He recently spent two years as a visiting researcher with the Office of Financial Research in the U.S. Treasury Department. He currently directs the Masters of Science in Business Analytics program at Brandeis, and is part of a Brandeis interdisciplinary research and teaching group interested in modeling dynamics in a wide range of fields. LeBaron’s research has concentrated on the issue of nonlinear behavior of financial and macroeconomic time series. He has been influential both in the statistical detection of nonlinearities and in describing their qualitative behavior in many series. LeBaron’s current interests are in understanding the quantitative dynamics of interacting systems of adaptive agents and how these systems replicate observed real world phenomenon. Also, LeBaron is interested in understanding some of the observed behavioral characteristics of traders in financial markets.
John Miller is Professor at Carnegie Mellon, External Professor at Santa Fe Institute and chair of its Science Steering Committee. His research focuses on the complex adaptive behavior that emerges in social systems. The goal of this work is to understand the principles by which aggregate patterns emerge from the simple interactions of individual adaptive agents. The nonlinear and disequilibrium nature of complex adaptive systems often necessitates new methodological and theoretical directions. Methodologically, computational methods provide a convenient tool for modeling such systems. Theoretically, standard analytic tools, based on both linearity and equilibrium behavior, may be ill-tuned to further our understanding of complex systems. Thus, new approaches that emphasize nonlinearities and dynamics are needed.
Complementing the above work, he has also pursued experimental and pure mathematical approaches to many of the above issues. Experimentally, colleagues and I are trying to uncover the rational limits of cooperation. Mathematically, we are working on a precise characterization of the dynamic behavior of complex adaptive systems. This work, which incorporates results from theoretical physics, chemistry, and biology, attempts to uncover new mathematical models that unify seemingly disparate adaptive systems.
Ole Peters is a Fellow at the London Mathematical Laboratory and the Principal Investigator of its economics program, and External Professor at Santa Fe Institute. He works on different conceptualizations of randomness in the context of economics. His thesis is that the mathematical techniques adopted by economics in the 17th and 18th centuries are at the heart of many problems besetting the modern theory. Using a view of randomness developed largely in the 20th century he has proposed an alternative solution to the discipline-defining problem of evaluating risky propositions. This implies solutions to the 300-year-old St. Petersburg paradox, the leverage optimization problem, the equity premium puzzle, and the insurance puzzle. It leads to deep insights into the origin of cooperation and the dynamics of economic inequality. He maintains a popular blog that also hosts the economics lecture notes.
Woody Powell is Professor of Education and (by courtesy) Sociology, Organizational Behavior, Management Science and Engineering, and Communication at Stanford University, and External Professor at Santa Fe Institute. He is co-director of the Stanford Center on Philanthropy and Civil Society. He joined the Stanford faculty in July 1999, after previously teaching at the University of Arizona, MIT, and Yale. He has been a fellow at the Center for Advanced Study in the Behavioral Sciences three times, and a visiting fellow at the Institute for Advanced Studies in Vienna twice. Powell has received honorary degrees from Uppsala University, the Helsinki School of Economics, and Copenhagen Business School, and is a foreign member of the Swedish Royal Academy of Sciences. He is a U.S. editor for Research Policy, and has been a member of the board of directors of the Social Science Research Council since 2000.
Powell is widely known for his contributions to institutional analysis, beginning with his article with Paul DiMaggio, "The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields" (1983) and their subsequent edited book, The New Institutionalism in Organizational Analysis (1991). Recent work with Jeannette Colyvas and Jason Owen-Smith looks at the genesis of practices that subsequently become deemed appropriate and accepted as taken for granted, and how relational patterns congeal into institutional logics. This work examines the micro-processes through which ideas and practices emerge, and how divergent views become "settled". Networks of affiliations often serve as the pulse of these social dynamics, but our work emphasizes that these structural patterns are deeply entwined with legitimating accounts that justify and interpret behaviors.
William Rand is Associate Professor of Marketing in the Department of Business Management at North Carolina State University. He examines the use of computational modeling techniques, such as agent-based modeling, machine learning, network analysis, natural language processing, and geographic information systems, to help understand and analyze complex systems, such as the diffusion of information, organizational learning, and economic markets.
He also works to develop methods, create pedagogy, and build frameworks to allow researchers and practitioners to use analytics and data-intensive methods in their own work.
He has received funding for his research from the NSF, DARPA, ARL, Google, WPP, and the Marketing Science Institute. His work has been published in JM, JMR, IJRM, Management Science, and JOM.
He received his doctorate in Computer Science from the University of Michigan in 2005 and prior to coming to NC State was at the University of Maryland for eight years.
Rajiv Sethi is a Professor of Economics at Barnard College, Columbia University and an External Professor at Santa Fe Institute. He has previously held visiting positions at Microsoft Research in New York City, and at the Institute for Advanced Study in Princeton. He is on the editorial boards of the American Economic Review and Economics and Philosophy. His current research deals with information and beliefs.
In collaboration with Brendan O’Flaherty, he has examined the manner in which stereotypes affect interactions among strangers, especially in relation to crime and the criminal justice system. These include interactions between victims and offenders, officers and suspects, prosecutors and witnesses, and judges and defendants. Their book, Shadows of Doubt: Stereotypes, Crime, and the Pursuit of Justice will be published by Harvard University Press in 2019.
Cosma Shalizi is Associate Professor in the Statistics Department at Carnegie Mellon University and External Professor at Santa Fe Institute. Most of his work involves stochastic aspects of nonlinear dynamical systems, unsupervised machine learning, or some combination of the two; almost all of it uses information theory, which he finds to be an invaluable tool for proving probabilistic results. His original training is in the statistical physics of complex systems — high-dimensional systems where the variables are strongly interdependent, but cannot be effectively resolved into a single low-dimensional subspace. He was (and is) particularly fond of the method of symbolic dynamics, and of cellular automata, which are spatial stochastic processes modeling pattern formation, fluid flow, magnetism and distributed computation, among other things.
Over the last several years, he has moved away from the mathematics of optimal prediction, towards devising algorithms to identify such predictors from finite data, and applying those algorithms to concrete problems. On the algorithmic side, he and Kristina Klinkner devised an algorithm, CSSR, which exploits the formal properties of the optimal predictive states to efficiently reconstruct them from discrete sequence data, and used large deviations arguments to show asymptotic convergence. He is writing a book on the statistical analysis of complex systems models.
Geoffrey West is the Shannan Distinguished Professor and former President of the Santa Fe Institute and Associate Senior Fellow of Oxford University’s Green-Templeton College. His BA is from Cambridge and his PhD from Stanford, where he later returned to join the faculty. West is a theoretical physicist whose primary interests have been in fundamental questions ranging from the elementary particles and their cosmological implications to universal scaling laws in biology and a quantitative science of cities, companies and global sustainability. His work is motivated by the search for “simplicity underlying complexity.” His research includes metabolism, growth, aging and lifespan, sleep, cancer and ecosystems, the dynamics of cities and companies, rates of growth and innovation, and the accelerating pace of life.
West has given many lectures world-wide including Davos and TED. Among his awards are the Mercer Prize from the Ecological Society of America, the Weldon Prize for Mathematical Biology, the Glenn Award for Aging Research and the Szilard Award from the American Physical Society. He has been featured in many publications world-wide including the New York Times, Financial Times, Wired, Time, The Economist, Nature and Science and participated in television productions including Nova, National Geographic and BBC. He is the author of the best-selling book Scale. His public service includes serving on the Council of the World Economic Forum. His work was selected as a breakthrough idea by the Harvard Business Review in 2006 and he was on Time magazine’s list of “100 Most Influential People in the World” in 2007.
David Wolpert is a Professor at Santa Fe Institute. He is an IEEE fellow, is the author of three books and more than 200 papers, has three patents, is an associate editor at more than half a dozen journals, and has received numerous awards. He has more than 17,000 citations in a wide range of fields, including physics, machine learning, game theory, information theory, the thermodynamics of computation, and distributed optimization. In particular, his machine learning technique of stacking was instrumental in both winning entries for the Netflix competition, and his papers on the no free lunch theorems jointly have more than 7,000 citations.
He is a world expert on using nonequilibrium statistical physics to analyze the thermodynamics of computing systems; extending game theory to model humans operating in complex engineered systems; exploiting machine learning to improve optimization; and Monte Carlo methods.
Previously he was the Ulam Scholar at the Center for Nonlinear Studies at Los Alamos National Laboratory, and before that he was at the NASA Ames Research Center and was a consulting professor at Stanford University, where he formed the Collective Intelligence Group. He has worked at IBM and at a data mining startup, and he is external faculty at numerous international institutions. His degrees in physics are from Princeton University and the University of California.