Dr. Morckel uses spatial and statistical methods to examine ways to improve quality of life for people living in shrinking, deindustrialized cities in the Midwestern United States. She is especially interested in the causes and consequences of population loss, including issues of vacancy, blight, and neighborhood change.
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.
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.
Joseph Ryan, PhD, is Associate Professor of Social Work, School of Social Work and Faculty Associate in the Center for Political Studies, ISR, at the University of Michigan, Ann Arbor.
Prof. Ryan’s research and teaching build upon his direct practice experiences with child welfare and juvenile justice populations. Dr. Ryan is the Co-Director of the Child and Adolescent Data, an applied research center focused on using big data to drive policy and practice decisions in the field. Dr. Ryan is currently involved with several studies including a randomized clinical trial of recovery coaches for substance abusing parents in Illinois (AODA Demonstration), a foster care placement prevention study for young children in Michigan (MiFamily Demonstration), a Pay for Success (social impact bonds) study focused on high risk adolescents involved with the Illinois child welfare and juvenile justice system and a study of the educational experiences of youth in foster care (Kellogg Foundation Education and Equity). Dr. Ryan is committed to building strong University and State partnerships that utilize big data and data visualization tools to advance knowledge and address critical questions in the fields of child welfare and juvenile justice.
Dr. Nalliah’s research expertise is process evaluation. He has studied various healthcare processes, educational processes and healthcare economics. Dr. Nalliah’s research studies were the first time nationwide data was used to highlight emergency room resource utilization for managing dental conditions in the United States. Dr. Nalliah is internationally recognized as a pioneer in the field of nationwide hospital dataset research for dental conditions and has numerous publications in peer reviewed journals. After completing a masters degree at Harvard School of Public Health, Dr. Nalliah’s interests have expanded and he has studied various public health issues including sports injuries, poisoning, child abuse, motor vehicle accidents and surgical processes (like stem cell transplants, cardiac valve surgery and fracture reduction). National recognition of his expertise in these broader topics of medicine have given rise to opportunities to lecture to medical residents, nurse practitioners, students in medical, pharmacy and nursing programs about oral health. This is his passion- that his research should inform an evolution of health education curriculum and practice.
Dr. Nalliah’s professional mission is to improve healthcare delivery systems and he is interested in improving processes, minimizing inefficiencies, reducing healthcare bottlenecks, increasing quality, and increase task sharing which will lead to a patient-centered, coherent healthcare system. Dr. Nalliah’s research has identified systems constraints and his goal is to influence policy and planning to break those constraints and improve healthcare delivery.
Jessica K. Camp, PhD, is Assistant Professor of social work in the Department of Health and Health Services at the University of Michigan, Dearborn.
Her research focuses on using large nationally representative data from the United States and internationally (SIPP, ACS, GSOEP) to explore trends in poverty and inequality. Specifically, I examine ways that marginalized and hyper-marginalized groups experience economic disparity and labor market exclusion. My most recent completed study showed how welfare reform can have a powerful impact on the well-being of working women, especially women with vulnerabilities. My area of expertise as a data analyst is in complex samples, regression, and longitudinal models. I am hoping my future work will inform ways that “Big Data” can be used in social work research.
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.
Sy Banerjee studies the impact of mobile devices on consumer behavior and on the processing of signals emerging from location-based Social Media posts. He teaches a MBA class on digital marketing and Big Data and collaborates with researchers from Business, GIS and Computer Science. Some of his recent works include:
- Assessing Prime-Time for Geotargeting With Mobile Big Data, Sy Banerjee, Vijay Viswanathan, Kalyan Raman, Hao Ying, Journal of Marketing Analytics, 2013, Vol. 1(3), pp 174-183.
- “Visualizing active travel sentiment in an urban context” with Greg Rybarczyk, International Conference on Transport & Health MINETA Transportation Institute, San Jose, California, July 2016.
- “Assigning Geo-Relevance of Sentiments Mined from Location-Based Social Media Posts” with R. Sanborn and M. Farmer, in Advances in Intelligent Data Analysis XIV, LNCS
- “Understanding In-Store Consumer Experiences via User Generated Content from Social Media”, working paper with Karthik Sridhar and Ashwin Aravindakshan
- “Tweeted Customer Emotions as Currency for Competitive Performance: A Framework of Location-Based Social Media Listening”, working paper with Amit Poddar, Karthik Sridhar, Nanda Kumar
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).
Muzammil M. Hussain is an Assistant Professor of Communication Studies, and Faculty Associate in the Institute for Social Research at the University of Michigan. Dr. Hussain’s interdisciplinary research is at the intersections of global communication, comparative politics, and complexity studies. At Michigan, Professor Hussain teaches courses on research methods, digital politics, and global innovation. His published books include “Democracy’s Fourth Wave? Digital Media and the Arab Spring” (Oxford University Press, 2013), a cross-national comparative study of how digital media and information technologies have supported the opening-up of closed societies in the MENA, and “State Power 2.0: Authoritarian Entrenchment and Political Engagement Worldwide” (Ashgate Publishing, 2013), an international collection detailing how governments, both democracies and dictatorships, are working to close-down digital systems and environments around the world. He has authored numerous research articles, book chapters, and industry reports examining global ICT politics, innovation, and policy, including pieces in The Journal of Democracy, The Journal of International Affairs, The Brookings Institutions™ Issues in Technology and Innovation, The InterMedia Institute™s Development Research Series, International Studies Review, International Journal of Middle East Affairs, The Communication Review, Policy and Internet, and Journalism: Theory, Practice, and Criticism. His website is mmhussain.net, and he tweets from @m_m_hussain