Tuesday, January 10, 2012
Tuesday, January 17, 2012
Dragan Huterer, Assistant Professor of Physics, University of Michigan
Physics Nobel Prize awarded to Adam Riess, Saul Perlmutter, and Brian Schmid
For the discovery of the accelerating expansion of the Universe through observations of distant supernovae
In the late 1990s cosmologists discovered that the expansion of the universe is speeding up, not slowing down as expected. This discovery, honored with the Nobel Prize in 2011, has generated waves in the field of cosmology and presents us with a grand mystery: what is the origin and nature of Dark Energy, the stuff that causes the accelerated expansion?
Tuesday, January 24, 2012
Bill Rand, Assistant Professor, University of Maryland Smith School of Business
Authority, Trust and Influence: The Complex Network of Social Media
The dramatic feature of social media is that it gives everyone a voice; anyone can speak out and express their opinion to a crowd of followers with little or no cost or effort, which creates a loud and potentially overwhelming marketplace of ideas. Given this egalitarian competition, how do users of social media identify authorities in this crowded space? Who do they trust to provide them with the information and the recommendations that they want? Which tastemakers have the greatest influence on social media users? Using agent-based modeling, machine learning and network analysis we begin to examine and shed light on these questions and develop a deeper understanding of the complex system of social media.
Tuesday, January 31, 2012
Tuesday, February 14, 2012
Tuesday, February 21, 2012
Erik Goodman, Director, BEACON Center for the Study of Evolution in Action (An NSF Science and Technology Center)
Professor, ECE, ME, CSE
Michigan State University
Evolution in Action: Exploring Evolutionary Dynamics in both Biological and Computational Domains
Nearly 400 faculty, staff and students are now members of the recently founded BEACON Center for the Study of Evolution in Action, headquartered at MSU. They are joined by a strong commitment to multidisciplinary research, often coupling study of evolution going on in a natural system with evolution of self-replicating digital organisms. Students are cross-trained: biologists take a course on computational methods, programming, and digital models of evolution, while computer scientists take a course on evolutionary biology; a subsequent course joins them in teams to initiate research projects. Goodman will describe the kinds of multidisciplinary and multi-institutional collaborations that are occurring, working with evolving bacteria, phages, yeast, and higher organisms, and involving Avida, MSUâ€™s platform for digital evolution.
Tuesday, March 6, 2012
Tim Lewis, Associate Professor, University of California-Davis, Dept. of Mathematics
Phase-Constancy in Chains of Half-Center Oscillators: The Neural Mechanisms Underlying Coordinated Locomotion
A fundamental challenge in many areas of science is to understand how coordinated network activity arises from the network connectivity and the intrinsic properties of oscillating units. This challenge is of importance in Neuroscience. Neuronal networks that produce r hythmic motor behaviors, such as locomotion, provide important model systems to address this challenge. A particularly good model system for this purpose is the neural circuit underlying the coordinated rhythmic limb movements in the crayfish swimmeret system.
Limbs of crayfish, called swimmerets, move rhythmically in a metachronal wave that progresses from the back to front of the animal during forward swimming. The swimmerets paddle with the same period, but neighboring swimmerets maintain phase-lags of ~25% of the period. This coordination of limb movements is maintained over a wide range of frequency. In this talk, I will discuss recent experimental and theoretical work that provides insight into the mechanisms underlying this robustly stable phase-locked rhythm.
Tuesday, March 13, 2012
Russell Golman, Postdoctoral Associate, Department of Social and Decision Sciences, Carnegie Mellon University
"Curiosity, Information Gaps, and the Utility of Knowledge"
We examine the motives driving the desire for, or the desire to avoid, information. We propose an integrated theoretical framework that makes sense of, and generates novel predictions regarding, phenomena related to preference about information, going beyond the standard economic account that information is valuable to the extent that it aids decision making. In addition, people try to satisfy curiosity, the desire for information in the absence of material benefits; people seek out information about issues they like to think about and avoid information about issues they do not like to think about (the ostrich effect); and people tend to avoid (though in some cases actually prefer) making decisions when relevant probabilities are not known (ambiguity aversion). Our framework relies on the insights that knowledge has valence, that ceteris paribus people prefer to fill in information gaps, and that information affects the focus of attention as well as contributes to knowledge. We offer non-obvious, testable predictions, such as that people might avoid obtaining costless medical tests, yet they might well choose to be informed about the results if the tests had been conducted (and especially if they were confronted with a medical professional who knew the results). Our framework also helps to make sense of the observation that people often invest in, and enjoy, obtaining expertise in areas of knowledge, such as a taste for wine or ability to identify flora and fauna, that confer no benefits beyond the knowledge itself.
Tuesday, March 20, 2012
Siddharth Suri, Research Scientist, Yahoo! Research, New York
"Cooperation in Static and Dynamic Networks"
This talk describes the results of a series of web-based, behavioral experiments designed to understand people's ability to cooperate in static and dynamic networks. In the context of static networks, it was previously thought that cooperation should fare better in highly clustered networks such as cliques than in networks with low clustering such as random networks. To test this hypothesis, we conducted a series of experiments, in which 24 individuals played a local public goods game arranged on one of five network topologies that varied between disconnected cliques and a random regular graph. In contrast with previous theoretical work, we found that network topology had no significant effect on average contributions.
Since humans have a natural tendency to choose with whom to form new relationships and with whom to end established relationships, we also study cooperation in dynamic networks. Helping cooperators to mix assortatively is believed to reinforce the rewards accruing to mutual cooperation while simultaneously excluding defectors. Here we report on another series of human subjects experiments in which groups of 24 participants played a multi-player prisoner's dilemma game where, critically, they were also allowed to propose and delete links to players of their own choosing at some variable rate. Over a wide variety of parameter settings and initial conditions, we found that endogenous partner selection significantly increased the level of cooperation, the average payoffs to players, and the assortativity between cooperators.
Joint work with Jing Wang (NYU) and Duncan Watts (Yahoo! Research).
Tuesday, March 27, 2012
Claudio Cioffi-Revilla Director of the Center for Social Complexity George Mason University
What would the first comprehensive textbook in Computational Social Science look like? A special exclusive preview for CSCS Michigan students
CSCS Michigan students have been leading pioneers in Computational Social Science, as have Mason CSS students at our Center for Social Complexity and CSS Department. In this talk I will describe a new CSS textbook project to share with students, including detailed content, and invite feedback. The scientific paradigm is founded on Simon's theory of complex adaptive social systems, developed with formalisms and computational modeling.
Tuesday, April 3, 2012
Tim McKay, Arthur F. Thurnau Professor Physics, University of Michigan
What can we learn from 48,579 physics students: Learning Analytics at Michigan
A new field of Learning Analytics has emerged. Its goal is to deploy technology to collect and collate the richest possible portrait of the progress of students, to mine this data for new insights into what affects student success, and to support an array of interventions aimed at optimizing teaching and learning. In this talk I will give some details of an example done in the Physics Department, speculate about possible futures for this field, and describe a new opportunity for support of learning analytics projects here at Michigan. Higher education is a particularly complex, though structured environment, and I believe research projects of interest to scholars in many areas will be opened by this new initiative.
Tuesday, April 10, 2012