Northwestern Institute on Complex Systems

Robotics, mechanics, planning and control of robotic manipulation; self organized systems, particularly decentralized control of mobile sensor networks; motion planning and control for underactuated dynamic systems; physical human/robot interaction, industrial applications.

Social network analysis and complexity theory focused on understanding outstanding human achievement in finance, consulting science and the arts.

Dynamics of networked oscillators; synchronization; mathematical models of consensus in social systems; dynamics of geophysical networks

Complex networks in nature; system-level modeling of biological processes.  Integrative modeling of gene and protein interaction-networks, complex fluctuations in healthy physiologic systems.

Integration of experimental data with computational analysis to investigate dynamic regulation of complex biological systems. Specific applications to cancer and immunology.

Computational biology; inference and modeling of regulatory networks; cancer genomics; bioinformatics/biostatistical methods.

Dynamical phenomena in physics, biology, sociology, neuroscience and economics

Operations management, logistics and distribution management, design of communication networks and design of distribtuion networks, combinational optimization, supply chain risk.

Social and knowledge networks:theories, statistical and computational methods: organizational theory.

Political institutions, the interaction of business and politics, crisis leadership, reputation management, integrated strategy and strategic aspects of corporate social responsibility.

Nonlinear systems and control theory; robust, adaptive and optimal control theory; stability and performance of interconnected systems;decentralized control and estimation

Stochastic modeling and its applications in production, service operations systems, management of health care access operations, manufacturing and supply chain management.

Computational neuroscience, fiber optics, wave propagation, nonlinear dynamics, complex systems.

Mathematical and computational modeling; social dynamics, spread of technologies and behaviors, tipping points, combining forecasts, markets with positive feedbacks.

Complex systems and nonlinear phenomena, primarily in the realms of chaos, fractals, statistical physics, complex networks and biological physics.

Complex systems, dynamics of granular matter, mixing and segregation.

Language evolution, textmining, automatic speech recognition, and word games.

Social networks, statistical network formation, strategic behavior in social contexts, repeated interactions, game theory and microeconomics

Mathematics and science education in the context of computation, connected learning, constructionism, computer-based modeling, agent-based modeling and complex systems and education.

Reproductive endocrinology, female reproductive health and infertility, oncofertility

Understanding how cities work and the future of science.  In addition, he writes for popular audiences as a contributor to Wired, and his essays about math and science have appeared in such places as the New York Times, The Atlantic, and the Ideas section of the Boston Globe. Arbesman is the author of The Half Life of Facts, about how knowledge changes over time.

Thermodynamics; thermoelasticity; phase transitions; structure, composition and dynamics of planetary interiors; body-wave seismology;subduction processes; networks and complex systems.

Cell motility; cell movement during morphogenesis; molecular genetics of motor molecules; myosin;dyein; molecular motors and disease.

Syntactic variation and change, semantics, pragmatics.

Psycholinguistics, cognitive neuropsychology, computational modeling, phonology.

Complex dissipative systems, theory of non-equilibrium self organization, and self-assembly.

Social and policy implications of information technology.

Neurobiology and biomechanics of active senasing behaviors, the development of bio-inspired computational models and hardware to test candidates neurobiological algorithms.

Regulatory reform and restructuring, particularly of network industries.

Complexity and chaos in granular and fluid flows; pattern formation; mixing and segregation; discrete-element simulation, experiements and theory of granular flows; mixing by cutting and shuffling.

Regulation and function of molecular chaperones.

Literacy theory (especially narrative); the history of ideas, both Russian and European; literary genres (especially satire, utopia and the novel); Chekhov, Gogol, Dostoevsky and Tolstoy.

Complex networks, nonlinear dynamics, and chaos.  Structure-dynamics relation in networks of dynamical systems.  Synchronization of coupled oscillators, with application to power grids.

Nonlinear optical response properties of molecules'electron transfer and molecular electronics, dynamics of polymer electrolyte transport'self-consistent field models for coupled vibration reaction dynamics; mean-field models for extended systems, including proteins and molecular assemblies'photonics in nanoscale systems; energetics of DNA/protein binding.

Information aspects of the theory of economic organization; the application of mathematical methods to the study of operations.

Computational Neuroscience: dynamics of neuronal networks with heterogeneous connectivity, information processing by neuronal networks in the olfactory bulb, and adaptive neural networks.  Pattern formation: spatially extended dynamical systems, bifucation theory with symmetry, complex patterns, spatio-temporal chaos.

Using theory and computation to describe physical phenomena in a broad range of applications relevant to chemistry, physics, biology and engineering.

Nonlinear dynamics and its applications, pattern formation, bifurcation theory, delay equations, feedback control, mathematical modeling of biological processes and of climate change.

Design and operations of logistics network; vehicle routing and scheduling; supply-chain management; applications in commercial and non-profit settings; transporation systems.

Application of statistical mechanics to the analysis of complex systems, the study of neural networks.

Statistics and public policy with a special focus in the design and evaluation of large-scale statistical data programs.

Operations management (capacity, inventory and supply chain management: queuing news vendor and heavy traffic theory and optimization), operations strategy (capacity investment, network design, strategic sourching, pricing)

My interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization (glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions), and more.

I received my PhD from Indian Institute of Technology Madras on Dec. 2009.  Between Feb. 2010 and Jan. 2012 I worked in the Amaral lab as a post-doc.  Currently I am a post-doc at Kellogg School of Management and NICO, working with Prof. Brian Uzzi.  My research interest are on physics of complex systems, statistical physics, visualization of complex networks and sports.

My main research interest is the empirical and theoretical analysis of Social and Information Networks.  I am particularly interested in the study of network evolution and information diffusion.

Nick Switanek is Visiting Assistant Professor of Management and Organizations. He received his Ph.D. in Organizational Behavior from Stanford University Graduate School of Business, his M.S. in Statistics from Stanford University, and his B.A. and B.S. from the University of Arizona. Professor Switanek’s research and teaching explore the intersection of organization theory, management strategy, and environmental sustainability.

The study of poverty, through social-network, resource-based and contextual perspectives is very interesting to me, and that is where most of my research is.

Alex Bentley is Professor of Anthropology and Archaeology at the University of Bristol. This Fall he is a Visiting Scholar at Northwestern University, spending time in both the Anthropology Department and NICO. In the U.K., Bentley is Deputy Director of a 5-year, interdisciplinary program to study 'Tipping Points' in environment and society (www.dur.ac.uk/ihrr/tippingpoints), a project that integrates work on climate change, the banking crisis, and the spread of fashions. Bentley has applied his research in projects with the British Department of Health, the Gates Foundation and commercial organisations. His new book, with Mark Earls and Michael O'Brien, is "I'll Have What She's Having: Mapping Social Behavior" (MIT Press).

Dr. Huepe obtained his PhD in Physics at the Ecole Normale Superieure in Paris, after completing undergraduate studies in his native Chile.  Dr. Cristian Huepe is a physicist conducting research in complex systems, nonlinear dynamics and statistical physics.  He has worked in various subjects throughout his career, including:superfluidity, Bose-Einstein condensates, a toy cosmology model, finite-time singularities, spatiotemporal chaos, defect dynamics and Faraday waves.  His current research focuses on the dynamics of collective motion and complex networks.

Jarrett Spiro is Assistant Professor of Organisational Behaviour at INSEAD. He received his PhD from the Graduate School of Business at Stanford University. He also holds a master's degree in Sociology from Stanford University. His teaching focuses on organization management theory and social network analysis.

Professor Spiro's research has covered a number of theoretical arenas including: network emergence, network dynamics, network methodology, complexity theory, the origins of innovation, and organizational form emergence and other dynamics. This work has examined several areas including the Broadway musical industry, the U.S. Film industry, and health organizations.

Dynamical processes and statistical properties of natural language, including language change, spreading of linguistic inovations, burstiness of words.

Analysis of extreme events in social systems including its dynamical origins, recurrence properties, prediction, and reactions.

Chaos in Hamiltonian systems, including billiards, stickiness in systems with mixed phase space, Poincare recurrence time, and optical cavities. A visual introduction to some of this topic you can find  at: Visualization of dynamical systems: Billiards |Recurrences 

Economic sociology, networks, institutional change, entrepreneurship, financial markets.  My research engages ideas from organization theory, economic sociology, and network analysis to explain the emergence of social structures in new and dynamic industries.

Roger Guimerà (Barcelona, 1976) graduated in Physics at Universitat de Barcelona in 1998, and obtained a PhD in Chemical Engineering from Universitat Rovira i Virgili in 2003. He then moved to Northwestern University, where he worked as a postdoctoral fellow and, later, as a Fulbright Scholar. In 2008 he became a Research Assistant Professor at Northwestern’s department of Chemical and Biological Engineering, before accepting his current position at ICREA.

I am an Assistant Professor in the School of Public Affairs at Arizona State University and the Associate Director for Policy Informatics at the ASU Decision Theater.  Prior to coming to ASU, I was a Visiting Assistant Professor at the Kellogg School of Management, and a Postdoctoral Research Fellow at Kellogg’s Ford Center for Global Citizenship.

My research addresses the theoretical and methodological challenges involved with studying how social and economic systems change.  The underlying motivation for my work is the desire to understand why well-intentioned organizational and public policies often provoke resistance and unanticipated responses by the system they are trying to improve. I view understanding the connection between individual and collective behavior as central to understanding this problem, and consequently use tools like agent-based modeling and social network analysis that foreground the interactions between individuals in a social system.

William Rand examines the use of computational modeling techniques, like agent-based modeling, geographic information systems, social network analysis, and machine learning, to help understand and analyze complex systems, such as the diffusion of innovation, organizational learning, and economic markets. He serves as the Director of the Center for Complexity in Business, the first academic research center focused solely on the application of complex systems techniques to business applications and management science. He also has an appointment with the University of Maryland Institute for Advanced Computer Studies, and affiliate appointments with the Departments of Decision, Operations & Information Technology and Computer Science.

Mark Rivera has a PhD from the Kellogg School of Management. His research draws from sociology, social-psychology, and statistical physics to understand how people form social networks and how these connections affect creativity, achievement, and job-satisfaction for people and for organizations.

I am mainly interested in understanding the emerging processes shaping complex socio-economic and ecological systems. My research has been focused on the analysis of declining networks, principles of bilateral cooperation between animals and between organizations, and dynamics in voting networks. I am also looking at transmission processes of information/errors, differences between status and reputation, and trying to add new research interests to my list.

Marta Sales-Pardo (Barcelona, 1976) graduated in Physics at Universitat de Barcelona in 1998, and obtained a PhD in Physics from Universitat de Barcelona in 2002. She then moved to Northwestern University, where she first worked as a postdoctoral fellow and, later, as a Fulbright Scholar. In 2008, she became a Research Assistant Professor at the Northwestern University Clinical and Translational Science Institute with joint appointments in the Department of Chemical and Biological Engineering and the Northwestern Institute on Complex Systems. In 2009, she accepted her current posistion as an Associate Professor in the Departament d’Engineyria Química at Universitat Rovira i Virgili.

Mike Stringer is co-founder and managing partner. A physicist gone wild, Mike is passionate about realizing the potential for big data analytics to make a positive impact on business and society. Despite wearing a suit occasionally, he still finds the time to argue with others about Bayesian statistics, explore the amazing food in Chicago, and has recently become fascinated with typography. Mike received a BS in Engineering Physics from the University of Colorado and a PhD in physics from Northwestern University.

Analysis of biological/biochemical networks