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Tim Cernak

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Tim Cernak, PhD, is Assistant Professor of Medicinal Chemistry with secondary appointments in Chemistry and the Chemical Biology Program at the University of Michigan, Ann Arbor.

The functional and biological properties of a small molecule are encoded within its structure so synthetic strategies that access diverse structures are paramount to the invention of novel functional molecules such as biological probes, materials or pharmaceuticals. The Cernak Lab studies the interface of chemical synthesis and computer science to understand the relationship of structure, properties and reactions. We aim to use algorithms, robotics and big data to invent new chemical reactions, synthetic routes to natural products, and small molecule probes to answer questions in basic biology. Researchers in the group learn high-throughput chemical and biochemical experimentation, basic coding, and modern synthetic techniques. By studying the relationship of chemical synthesis to functional properties, we pursue the opportunity to positively impact human health.

Samuel K Handelman

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Samuel K Handelman, Ph.D., is Research Assistant Professor in the department of Internal Medicine, Gastroenterology, of Michigan Medicine at the University of Michigan, Ann Arbor. Prof. Handelman is focused on multi-omics approaches to drive precision/personalized-therapy and to predict population-level differences in the effectiveness of interventions. He tends to favor regression-style and hierarchical-clustering approaches, partially because he has a background in both statistics and in cladistics. His scientific monomania is for compensatory mechanisms and trade-offs in evolution, but he has a principled reason to focus on translational medicine: real understanding of these mechanisms goes all the way into the clinic. Anything less that clinical translation indicates that we don’t understand what drove the genetics of human populations.

Antonios M. Koumpias

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Antonios M. Koumpias, Ph.D., is Assistant Professor of Economics in the department of Social Sciences at the University of Michigan, Dearborn. Prof. Koumpias is an applied microeconomist with research interests in public economics, with an emphasis on behavioral tax compliance, and health economics. In his research, he employs quasi-experimental methods to disentangle the causal impact of policy interventions that occur at the aggregate (e.g. states) or the individual (e.g. taxpayers) level in a comparative case study setting. Namely, he relies on regression discontinuity designs, regression kink designs, matching methods, and synthetic control methods to perform program evaluation that estimates the causal treatment effect of the policy in question. Examples include the use of a regression discontinuity design to estimate the impact of a tax compliance reminders on payments of overdue income tax liabilities in Greece, matching methods to measure the influence of mass media campaigns in Pakistan on income tax filing and the synthetic control method to evaluate the long-term effect of state Medicaid expansions on mortality.

Evolution of Annual Changes in All-cause Childless Adult Mortality in New York State following 2001 State Medicaid Expansion

Jinseok Kim

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Jinseok Kim, Ph.D., is Research Assistant Professor in the Institute for Social Research at the University of Michigan, Ann Arbor.  Prof. Kim works on resolving named entity ambiguity in large-scale scholarly data (publication, patent, and funding records) in digital libraries. Especially, his current research is focused on developing methods for disambiguating author and affiliation names at a digital library scale using various supervised machine learning approaches trained on automatically labeled data . Disambiguated data from multiple sources will be integrated to be analyzed for insights into research production, scientific collaboration, funding evaluation, and research policy at a national level.

Brian P. McCall

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My interests are in the areas of labor economics, program evaluation, and the economics of education. Currently my research focuses on college student debt accumulation and the subsequent risk of default, the effect of tuition subsidies on college attendance, the influence of family wealth on college attendance and completion, the effect of financial aid packages on college attendance, completion and subsequent labor market earnings, the influence of education on job displacement and subsequent earnings, the impact of unemployment insurance rules on unemployment durations and re-employment wages, and the determinants and consequences of repeat use of the unemployment insurance system.

Matthew A. Davis

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Dr. Davis is a health services researcher who has additional training in data science. His research focuses on leveraging large sources of data to study important policy-relevant issues. Dr. Davis has made several important contributions to a variety of areas including the identification of dietary sources of arsenic exposure in the US population, studying national use of health services over time for nonspecific back pain, and the development of methods to use social media data to measure social support and public opinion. A specific interest of Dr. Davis is the application of data mining methods to healthcare claims data. Funded by the NIH, his current work is investigating health service substitution for nonspecific back pain by conducting a natural experiment of Medicare patients. He received his Masters in Public Health from Dartmouth Medical School and his PhD in quantitative biomedical sciences from Dartmouth College.

Dr. Davis’s research has received national media attention on several occasions. Articles about his research have appeared in outlets including Forbes, The Huffington Post, USA Today, Time, The Atlantic, and Consumer Reports. His research has also been featured on NPR’s Marketplace and the Today Show.

Rocio Titiunik

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Prof. Titiunik’s research interests lie primarily in quantitative methodology for the social sciences, with emphasis on quasi-experimental methods for causal inference and political methodology. She is particularly interested in the application and development of non-experimental methods for the study of political institutions, a methodological agenda that is motivated by her substantive interests on democratic accountability and the role of party systems in developing democracies. Some of her current projects include the application of web scraping and text analysis tools to measure political phenomena.

Yi Lu Murphey

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Dr. Yi Lu Murphey is an Associate Dean for Graduate Education and Research, a Professor of the ECE(Electrical and Computer Engineering) department and the director of the Intelligent Systems Lab at the University of Michigan, Dearborn. She received a M.S. degree in computer science from Wayne State University, Detroit, Michigan, in 1983, and a Ph.D degree with a major in Computer Engineering and a minor in Control Engineering from the University of Michigan, Ann Arbor, Michigan, in 1989. Her current research interests are in the areas of machine learning, pattern recognition, computer vision and intelligent systems with applications to automated and connected vehicles, optimal vehicle power management, data analytics, and robotic vision systems. She has authored over 130 publications in refereed journals and conference proceedings. She is an editor for the Journal of Pattern Recognition, a senior life member of AAAI and a fellow of IEEE.

Srijan Sen

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Srijan Sen, MD, PhD, is the Frances and Kenneth Eisenberg Professor of Depression and Neurosciences. Dr. Sen’s research focuses on the interactions between genes and the environment and their effect on stress, anxiety, and depression. He also has a particular interest in medical education, and leads a large multi-institution study that uses medical internship as a model of stress.

Michael Traugott

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Michael Traugott, PhD, is Professor Emeritus of Communication Studies, Professor Emeritus of Political Science, College of Literature, Science, and the Arts, Research Professor Emeritus, Center for Political Studies and Adjunct Research Professor, Center for Political Studies, Institute for Social Research.

Professor Traugott studies the mass media and their impact on American politics. This includes research on the use of the media by candidates in their campaigns and its impact on voters, as well as the ways that campaigns are covered and the impact of this coverage on candidates. He has a particular interest in the use of surveys and polls and the way news organizations employ them to cover campaigns and elections.