Fall 2010 Talk Series on
Networks and Complex Systems
Every Monday 6-7p, Wells Library 001 ~ Optional Dinner at at Lennie's
This talk series is open to all Indiana University faculty and students interested in network analysis, modeling, visualization, and complex systems research. A major intent is to cross-fertilize between research done in the social and behavioral sciences, research in natural sciences such as biology or physics, but also research on Internet technologies. See also the Wikipedia entries on graph theory, small world networks, power law, and complex networks, and self organizing systems.
Katy Börner <firstname.lastname@example.org> Victor H. Yngve Professor of Information Science, Cyberinfrastructure for Network Science Center, SLIS, IUB.
Time & Place
Every Monday 6:00-7:00pm in the Wells Library (formerly Main Library) at
Indiana University, Bloomington, Room 001. Right after the Cognitive
Science Colloquium Series. There is an optional dinner afterwards 7:00-9:00pm
Fall 2004 | Spring
2005 | Fall 2005 |
Spring 2006 | Fall 2006 | Spring 2007 | Fall 2007 | Spring 2008 | Fall 2008
| Spring 2009 | Fall 2009
Related Courses at IUB
in Spring 2010
- S604 Metadata & Semantics by Ying Ding, SLIS
- COGS-Q580 An Introduction to Dynamical Systems in Cognitive Science by Randall Beer, Cognitive Science, Computer Science, and Informatics at IU
- COGS-Q700 Introduction to Embodied Cognitive Science by Randall Beer, Cognitive Science, Computer Science, and Informatics
- S604 The Semantic Web by John Paolillo, SLIS & Informatics
- I485/I585 Biologically-Inspired Computing by Luis Rocha, Informatics
- INFO I400 Linked: the science of networks from the social atom to Facebook by Fil Menczer and Alex Vespignani, Informatics
- S604 Modeling and Simulation of Social and Organizational Behavior by Hamid Ekbia, SLIS
- P575 Biophysics by Sima Setayeshgar, Physics
- VSCI-V 768 MATLAB by Nicholas Port, Optometry
- P747 Complex Adaptive Systems by Eliot Smith & Robert Goldstone, Psychological and Brain Sciences
- I590 The Simplicity of Complexity by Alessandro Vespignani & Alessandro Flammini, Informatics
- I601 Introduction to Complexity by Alessandro Vespignani & Alessandro Flammini, Informatics
- I486 /I586 Artificial Life as an approach to Artificial Intelligence, Larry Yaeger, Informatics
- STAT 482/S682 Topics in Mathematical Statistics: Model Selection Methods by Guilherme Rocha,
- B669 Data Mining by Dirk Van Gucht, Computer Science
- P438 Fundamentals of Computer Networks by Raquel Hill, Computer Science
- P538: Computer Networks by Minaxi Gupta, Computer Science
- P582 Biological and Artificial Neural Networks by John Beggs, Physics
- I486/I586 Artificial Life as Approach to AI by Larry Yaeger, Informatics (each Spring)
- S637 Information Visualization by Katy Börner, SLIS (each Spring)
- Y673 Networks and Institutions by Armando Razo, Department of Political Science and the Workshop in Political Theory and Policy Analysis
- D318 3D Computer Graphics by Margaret Dolinsky, FINA
- D510 Digital Art: Advanced Practice by Margaret Dolinsky, FINA
- S660 Social Networks in Sociology, by Bernice Pescosolido, Sociology
- P533/P534 Introduction to Bayesian Data Analysis I & II by John K. Kruschke (Spring 11)
- Econ 724 Network Formation Games by Frank Page, Economics
- P548 Introduction to Mathematical Biology by James Glazier, Physics (Spring 11)
- S636 Semantic Web by Ying Ding, SLIS
- B649 Internet Services & Protocols by Minaxi Gupta, Computer Science
- B553 Neural and Genetic Approaches to Artificial Intelligence by Mike Gasser, Computer Science
- STAT S475/S675: Statistical Learning and High-Dimensional Data Analysis by Michael Trosset,
- STAT S426/S626 Bayesian Theory and Data Analysis by Guilherme Rocha,
- I400/I590 (cross-listed in Cognitive Science) Seek and Find: Search Strategies in Space and Time by Peter M. Todd, Psychological and Brain Sciences, Cognitive Science & Informatics
- B656 Web Mining by Filippo Menczer, Informatics and Computing
- B689 Mathematical Modeling: Concepts, Programming, and Visualization by Andrew J. Hanson, Computer Science Program, School of Informatics and Computing
- S603 Agent-Based Modeling and GIS by Hamid Ekbia, SLIS (Summer Workshop)
- S604 Structural Data Mining & Modeling by Katy Börner, SLIS
- COGS-Q540 Foundations of Cognitive Science by Colin Allen, HPS
- COGS-Q700 Brain-Body-Environment Systems by Randall Beer, Cognitive Science, Computer Science, and Informatics (Fall 11)
Networks and Complex Systems Centers at Indiana University
Links to people, projects, groups, students, courses and news related to complex systems and networks research at Indiana University are also available via
This talk series is sponsored by the Cyberinfrastructure for Network Science Center and the School of Library and Information Science.
Related Talk Series
Colloquium on Complexity and Social Networks organized by David Lazer
at Harvard U
The Age of Networks speaker series organized by Noshir Contractor, UIUC & NCSA
NICO Seminars organized by NICO, Northwestern University
9/13 Guillherme Rocha, Department of Statistics, IU, Bloomington
Monitoring Civil Structures using Restricted autoregressive models and Wireless Sensor Networks
Abstract: Wireless Sensor Networks (WSNs) are a promising technology to detect changes in the state of a structure by monitoring its features such as its natural vibration properties. The natural vibration properties of the structure can be estimated using a multivariate autoregressive model (AR model) of its measured response to ambient vibrations. Fitting a multivariate AR model to the observed data requires the computation of the lagged covariance between measurements in all nodes. The resulting volume of data transmission causes significant latency due to the low data bandwidth of WSNs in addition to having a high transmission energy cost. In this talk, a set of physically motivated restrictions to the estimation of the AR model is presented. Such restrictions significantly reduce the volume of data flowing through the WSN, thus reducing the latency in obtaining modal parameters and extending the battery lifetime of the WSN. The stabilization plots for the restricted and full AR models fitted using data simulated from linear structures are compared. Data collected from a WSN deployed on the Golden Gate Bridge are used to compare the stabilization plots and the estimated modes using the restricted and full AR models. The comparisons show that the restricted form of the AR leads to estimates of the modal parameters of comparable quality to that of the full AR model while substantially reducing the volume of transmitted data.
Bio: Guilherme (G as in goal + Willliam) has a degree in Mechanical Engineering from the University of Sao Paulo in 1999, his M.S. in Economics from the Getulio Vargas Foundation in 2003 and a Ph.D. in Statistics from University of California, Berkeley in 2008. He joined IU as an Assistant Professor in August 2008 and is interested in statistical regularization methods and its applications to high dimensional and dynamical data sets.
9/20 Jan Reichelt, Co-Founder, Mendeley, Ltd.
Mendeley - A New Face of Science?
Abstract: Mendeley is social software for academics - as free and cross-platform reference management software Mendeley helps researchers and research groups to work smarter. Usage and article information is then anonymously aggregated on Mendeley Web, enabling researchers to discover real-time usage statistics, articles, and like-minded academics, thus making academic knowledge more transparent and accessible. Mendeley is on track to become the world's largest open research database, and everyone can access this data via Mendeley's API, to freely re-use the data and build applications on top of it. Is this model a new "face of science"?
Bio: Jan is Co-Founder and President of Mendeley, a fast-growing technology start-up that helps people to organize and collaborate on research projects, and that is creating the world's largest open research database. Jan already worked at Internet start-ups during the first dot com era. He studied Business Administration at the WHU Koblenz, the LUISS Rome, and the University of Bath, and graduated in 2004 as MBA with a focus on Electronic Business, Accounting, and Entrepreneurship. Currently, Jan is pursuing a Ph.D. in Information Management at the University of Cologne and spent some time as visiting researcher at the Indian Institute of Management, Bangalore. Previously, he was an advisor to a member of SAP’s supervisory board. He likes languages (especially Italian), Latin music, and sports.
9/27 Jon Corson-Rikert, Head of Information Technology Services and and Brian Lowe, Semantic Applications Team Lead for the VIVO project and a programmer/analyst in Cornell’s Mann Library, Cornell University
The VIVO project: Origins, growth, challenges, and opportunities
Abstract: Indiana University researchers Katy Börner and Ying Ding are leading visualization and ontology efforts respectively for the NIH-funded project, “VIVO: Enabling National Networking of Scientists.” The Indiana University Digital Library team lead by Robert McDonald is implementing the VIVO software for the project using data from IUs system of records such as the IU Adress book, Human Resources, and Sponsored Research. In this talk, two of the original developers of VIVO at Cornell University will discuss the creation of VIVO at Cornell, its development as a Semantic Web application, the challenges faced expanding a tool for a single discipline to the scope of a major university and beyond, and the opportunities for VIVO as an open-source project in the increasingly exciting arena of Linked Open Data (http://linkedata.org).
Jon Corson-Rikert is Head of Information Technology Services at Cornell University’s Mann Library and National Development Coordinator for the VIVO: Enabling National Networking of Scientists project. Jon received a B.A. in Visual Environmental Studies from Harvard University and worked in cartography, land information systems, GIS, and computer graphics before joining Mann Library in 2001. While at Mann Library he has implemented upgrades to the Cornell University Geospatial Information Repository, developed a hosting application for the eClips (http://eclips.cornell.edu) collection of digital video clips on entrepreneurship, business, and leadership, and initiated the VIVO software (http://vivo.cornell.edu) in 2003.
Brian Lowe is the Semantic Applications Team Lead for the VIVO project and a programmer/analyst in Cornell’s Mann Library. A graduate of Cornell University in linguistics, Brian has been a key contributor to the VIVO effort at Cornell and has strongly influenced the transition of VIVO from its original relational database implementation to a full Semantic Web application.
10/4 Brian Uzzi, Kellogg School of Management, Northwestern University
Instant-Messaging Networks and the Collective Genius of Profitable Day Traders (Paper)
Abstract: Synchronicity has been called one of the most pervasive and mysterious drives in nature because it can spontaneously arise without leadership to effectively govern group performance in systems facing uncertainty. To examine the possible role of sync and collective performance in collective human systems, we studied stock trading behavior, which shares basic conditions with animal systems of collaboration and competition that face uncertainty. Analyzing novel, stock trader data on $>1$ million moment-to-moment trades and $>2$ million instant messages, we report on the potential dynamics of human synchronicity and its association with collective performance. First, we find non-trivial synchronous human trading of different stocks across various time scales and alternative null models. Second, sync is positively related to performance but in a non-linear manner -- revealing an elusive property of sync found in some animal systems. Third, sync appears to arise without leadership or conscious coordination. Rather, sync emerges through traders' links to their separate instant messaging networks, which are used to disambiguate market information, and which appear to trigger sync when disambiguated market information is at its more advantageous point between risk and reward. This suggests that sync may have untapped benefits for complex human systems and that vanguard communication technology may furnish new opportunities for achieving collective performance in complex human systems.
Bio: Brian Uzzi is the Richard L. Thomas Distinguished chair in leadership at the Kellogg School of Management, Northwestern University. He also co-directs NICO, the Northwestern Institute in Complex systems and holds professorships in Sociology and in the McCormick School of Engineering. Over the years he has taught around the world and visited on the faculties of INSEAD, University of Chicago, and the University of California at Berkeley where he was the Warren E. and Carol Spieker Professor of Leadership in 2008. His award winning and highly cited research uses social network analysis and complexity theory to understand outstanding human achievement in finance, consulting science, and the arts. He earned his MS in social psychology from Carnegie-Mellon University and a Ph.D. in sociology from The State University of New York at Stony Brook.
10/11 No talk scheduled - Columbus Day
10/18 Jonathon Cummings, Associate Professor of Management, Fuqua School of Business, Duke University and Faculty Director, Center for Entertainment, Media, and Information Technology (EMIT)
Research Team Integration: What It Is and Why It Matters
Abstract: Science policy across the world emphasizes the desirability of research teams that can integrate diverse perspectives and expertise into new knowledge, methods, and products. However, integration in research work is not well understood. Based on retrospective interviews with 55 researchers from 52 diverse research projects, I will first present a study in which we categorized teams as co-acting (50%), administratively-integrated (15%), and operationally-integrated (35%). Integration, when it existed, began when PIs chose collaborators and pursued integration throughout the project. I will then describe researchers’ experiences with integration, and research climates that discouraged or encouraged it. Finally, I will note implications for policy choices and design, including changes in team structuring and technology support.
Bio: Jonathon Cummings is an Associate Professor of Management at the Fuqua School of Business, Duke University, and Faculty Director of the Center for Entertainment, Media, and Information Technology (EMIT). After completing his dissertation and post-doc at Carnegie Mellon University, he spent three years at the MIT Sloan School of Management as an Assistant Professor. During graduate school he interned at Intel (studying collaborative software) and at Motorola (studying knowledge management). His current research focuses on social networks and teams in corporations and science, and the role of knowledge sharing in work distributed across different geographic locations. His publications have appeared in journals ranging from Management Science to Research Policy to MIS Quarterly.
10/25 Joshua Danish, Assistant Professor of Learning Sciences, School of Education, IU, Bloomington
Complex Systems and Complex Representational Practices in Early Elementary Classrooms
Abstract: Traditionally, complex systems concepts are not presented to students until middle school at the earliest, with complex systems learning most common at the high school or college level. Yet the ability to understand a complex system from multiple levels of analysis, and to reason about its emergent properties, is of growing importance in science education. Therefore, it is worth asking whether or not complex systems can be taught in intellectually valid ways to children as early as kindergarten in an effort to help them develop early, generative conceptions of complex systems. I will present findings from two studies of the BeeSign simulation software (http://www.joshuadanish.com/beesign) and curriculum that were designed to help young children learn about how honeybees collect nectar from a complex systems perspective. I will also highlight the role of representing students’ developing understanding in the learning process.
The first study took place with 42 kindergarten and first-grade students at a progressive elementary school in Los Angeles. I first present findings that demonstrate that students demonstrated a statistically significant improvement of their understanding of the beehive complex system, using an interview coded for students’ understanding at the structure, behavior, and function level (Danish, 2009). I will then discuss the relationship between different forms of activity in which the students engaged and the different aspects of the content that they discussed. For example, individual drawings appear related to students’ understanding of the honeybee structures, while participatory models helped them link structures to behaviors, and inquiry with the BeeSign software supported students in discussing the honeybee hive from an aggregate level (Danish, 2009; under review).
As students engaged in creating representation of honeybees collecting nectar, their representational practices also changed, leading them to be more constructively critical of their peers’ work. I will summarize findings that detail the changes in students’ representational practices (Danish & Phelps, in press) and also the relationship between different representational contexts and students’ engagement with various aspects of representing (Danish, 2010). For example, students creating individual representations were more likely to focus on the “what” of their drawings while students creating skits would shift to discussions of “how” to represent aspects of their drawings and “why”.
I conclude with a brief discussion of a follow-up study that included 40 first- and second-grade students at a public school in Bloomington Indiana. In this study (Danish, Peppler, Phelps, & Washington, under review) I will highlight student improvement on a test sub-scale related to the aggregate behavior of the honeybee hive, and the role of the BeeSign software in supporting students’ inquiry into this content.
Bio: Joshua Danish is an Assistant Professor in the Learning Sciences program at Indiana University. The overarching theme in his program of research is an examination of how people learn through activity. Learning through activity involves interacting with other people, physical objects, and ideas. Physical objects can range from actual flowers and drawings that label their parts to computer simulations. Similarly, ideas include individual beliefs and preferences, the rules that groups such as classrooms follow, and historically developed concepts that span generations. His research examines how individuals coordinate their actions and ideas within these complex settings, and how this can lead to learning. A major focus of Joshua's work has been examining how young students (5-7 years old) create representations while learning about complex science concepts.
11/01 No Talk
11/15 No Talk
11/22 Faculty, Staff, and Students at IUB (4:00-6:00pm ~ Room LI001)
Networks and Complex Systems OPEN HOUSE
Abstract: Open your laptops and demo your software. Bring posters to introduce your research questions and results. Feel free to visit the IV/CNS Open House web site. There will be presentations of research and demos of diverse tools between 4:15p - 5:45p.
12/6 Badri Narayanan Gopalakrishnan, Research Economist and Database Manager, Center for Global Trade Analysis, Purdue University
The Global Trade Analysis Project
Abstract: GTAP (Global Trade Analysis Project) is a global network of researchers and policy makers conducting quantitative analysis of international policy issues. GTAP's goal is to improve the quality of quantitative analysis of global economic issues within an economy-wide framework. To accomplish this, GTAP offers data, models, resources, courses, conferences and research projects. GTAP Data Base is a global data base describing bilateral trade patterns, production, consumption and intermediate use of commodities and services. Its latest version has 112 regions and 57 sectors for a base year of 2004. The standard GTAP Model is a multiregion, multisector, computable general equilibrium model, with perfect competition and constant returns to scale. The data and models are continuously evolving with the efforts of the Center for Global Trade Analysis and the ever-expanding GTAP network, since 1993. Resources include the research work of over 8000 GTAP users all over the world, technical papers, working papers, data and model documentation and research memoranda. Short courses and conferences are held every year. In this talk, we will discuss the construction procedures in GTAP Data Base, features of GTAP model and an overview of other GTAP offerings.
Bio: Badri Narayanan Gopalakrishnan has been working at the center on the construction of GTAP database, its documentation, teaching in the courses and conducting research on various economic issues, particularly on international trade and industry-related issues using CGE and econometric models. His other areas of interests include Labour Economics, Productivity Analysis, Demand Analysis and Environmental Economics. He holds a PhD from IGIDR (Indira Gandhi Institute of Development Research), Mumbai. Prior to joining the center, Badri was with ICRIER (Indian Council for Research on International Economic Relations), New Delhi, as a Fellow, where he conducted a field-based study on the Indian Auto Industry for the Government of India and co-ordinated few other research projects in the areas of industry and finance. He was a Teaching Assistant in environmental economics and econometrics to the graduate students at IGIDR and was a part of the IGIDR team involved in some research projects for the Government of India. His Dissertation was on "Some Economic Issues in Indian Textile Sector". Badri also holds a B.Tech. in Textile Technology and has a brief industrial experience as a production manager in a garment export firm in India. He participated in a Meeting with the Nobel Laureates in Economic Sciences in Lindau, Germany in 2004. He was awarded a fellowship by Center for Global Trade Analysis at Purdue University, USA, for participating in a course on GTAP in 2005-06. He has many publications in national and peer-reviewed international journals and books. He has also presented many of his research papers in national and international conferences.
12/13 James Moody, Department of Sociology & Director of the Network Analysis Center, Duke University
Popularity Trajectories and Substance Use in early Adolescence
Abstract: This paper introduces new longitudinal network data from the
"Promoting School-Community-University Partnerships to Enhance Resilience"
or "PROSPER" peers project. In 28 communities, grade-level sociometric
friendship nominations were collected from two cohorts of middle school
students as they moved from 6th, to 9th grade. As an illustration and
description of these longitudinal network data, this paper describes the
school popularity structure, changes in popularity position, and suggests
linkages between popularity trajectory and substance use. In the
cross-section, we find that the network is consistent with a hierarchical
social organization, but exhibits considerable relational change in both
particular friends and position at the individual level. We find that both
the base level of popularity and the variability of popularity trajectories
effect substance use.
Bio: James Moody is professor of sociology at Duke University. He has published
extensively in the field of social networks and social theory. His work has
focused theoretically on the network foundations of social cohesion and
diffusion, with a particular emphasis on building tools and methods for
understanding dynamic social networks. He has used network models to help
understand school racial segregation, adolescent health, and the development
of social science disciplines. Moody's work is funded by the National
Science Foundation, the National Institutes of Health and the Robert Wood
Johnson Foundation. He is winner of INSNA's (International Network for
Social Network Analysis) Freeman Award for scholarly contributions to
network analysis and editor of the on-line Journal of Social Structure.