Kevin Quinn

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Kevin Quinn, PhD, is Professor of Political Science in the College of Literature, Science, and the Arts at the University of Michigan, Ann Arbor.

Prior to joining the Michigan faculty, Professor Quinn was a Professor of Law at UC Berkeley. His research focuses on questions of empirical legal studies and statistical methodology. His research has been supported by the National Science Foundation and has appeared in leading journals in political science, statistics, and law. Professor Quinn is a former President of the Society for Political Methodology and his research has received multiple professional awards.

Jowei Chen

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Jowei Chen, PhD, is Associate Professor of Political Science in the College of Literature, Science, and the Arts at the University of Michigan, Ann Arbor. Prof. Chen holds a secondary appointment in the Center for Political Studies in the Institute for Social Research.

Prof. Chen’s research focuses on political geography and political institutions in the United States. His work on legislative districts examines how the geography of Democrat and Republican voters, as well as the political manipulation of district boundaries, affects voters’ political representation in legislatures. This work uses individual-level and precinct-level data about elections, combined with computer simulations of the district-drawing process. Other research projects analyze the political composition of the federal workforce by analyzing the campaign contributions and partisanship of bureaucratic employees, linking employee records with voter registration records and campaign finance data.

 

 

Brian Min

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Brian Min, PhD, is Associate Professor of Political Science in the College of Literature, Science, and the Arts at the University of Michigan, Ann Arbor. Prof. Min holds secondary appointments as Research Associate Professor in the Center for Political Studies and the Institute for Social Research.

Prof. Min studies the political economy of development with an emphasis on distributive politics, public goods provision, and energy politics. His research uses high-resolution satellite imagery to study the distribution of electricity across and within the developing world. He has collaborated closely with the World Bank using satellite technologies and statistical algorithms to monitor electricity access in India and Africa, including the creation of a web platform to visualize twenty years of change in light output for every village in India (http://nightlights.io).

 

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Sebastian Zoellner

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Sebastian Zöllner is a Professor of Biostatistics. He also holds an appointment in the Department of Psychiatry. Dr. Zöllner joined the University of Michigan after a postdoctoral fellowship in the Department of Human Genetics at the University of Chicago. His research effort is divided between generating new methods in statistical genetics and analyzing data. The general thrust of his work is problems from human genetics, evolutionary biology and statistical population biology.

Walter Mebane

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My primary project, election forensics, concerns using statistical analysis to try to determine whether election results are accurate.  Election forensics methods use data about voters and votes that are as highly disaggregated as possible.  Typically this means polling station (precinct) data, sometimes ballot box data.  Data can comprises hundreds of thousands or millions of observations.  Geographic information is used, with geographic structure being relevant.  Estimation involves complex statistical models.  Frontiers include:  distinguishing frauds from effects of strategic behavior;  estimating frauds probabilities for individual observations (e.g., polling stations);  adjoining nonvoting data such as from in-person election observations.

Robert J. Franzese Jr.

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Exploring properties of spatial-econometric methods for valid estimation of interdependent processes, i.e., estimation of spatially & spatiotemporally dynamic responses, primarily in political science and political economy applications. Specific applications have included international tax-competition and national tax & other economic policies, U.S. inter-state policy diffusion, the (possibly contagious) spread of intra- and inter-state conflict.

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Josh Pasek

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Josh Pasek is Assistant Professor of Communication Studies and Faculty Associate in the Center for Political Studies at the University of Michigan.  His substantive research explores how new media and psychological processes each shape political attitudes, public opinion, and political behaviors.  Josh also examines issues in the measurement of public opinion including techniques for incorporating social trace data as a means of tracking attitudes and behaviors.  Current research evaluates whether the use of online social networking sites such as Facebook and Twitter might be changing the political information environment, and assesses the conditions under which nonprobability samples, such as those obtained from big data methods or samples of Internet volunteers can lead to conclusions similar to those of traditional probability samples.  His work has been published in Public Opinion Quarterly, Political Communication, Communication Research, and the Journal of Communication among other outlets.  He also maintains two R packages for producing survey weights (anesrake) and analyzing weighted survey data (weights).

Arun Agrawal

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Arun Agrawal, PhD, is the Samuel Trask Dana Professor in the School of Environment and Sustainability at the University of Michigan, Ann Arbor.  Prof. Agrawal emphasizes the politics of international development, institutional change, and environmental conservation in his research and teaching. He has written critically on indigenous knowledge, community-based conservation, common property, population resources, and environmental identities. Prof. Agrawal is the coordinator for the International Forestry Resources and Institutions network and is currently carrying out research in central and east Africa as well as South Asia. Since 2013, Prof. Agrawal has served as the editor-in-chief of World Development and his recent work has appeared in Science, PNAS, Conservation Biology, Development and Change, among other journals. Preceding his work at U-M, Prof. Agrawal was educated at Duke University, the Indian Institute of Management, and Delhi University and has held teaching and research positions at Yale, Florida, McGill, Berkeley, and Harvard among other universities.

Selected papers and book chapters are available online and can be accessed at this link.

Additional science information available at World Science News

 

Yves Atchade

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My current research explores the possibilities and limits of Markov Chain Monte Carlo (MCMC) methods in dealing with posterior or quasi-posterior distributions that arise from high-dimensional Bayesian (or quasi-Bayesian) inference in regression and graphical models. I also have some interests in optimization, and these revolve around the use of stochastic methods: whether (and how) the use of stochastic methods can help tackle large scale optimization problems of interest in statistics. I also have interests in the use of remote sensing data to study social and environmental issues in Africa.