The SoDa Center will recruit a variety of faculty, staff, and students to engage with the Center and its mission in a variety of ways.
SoDa is affiliated with the International Program in Survey and Data Science.
Katharine G. Abraham is a Distinguished University Professor. Her published research includes papers on the work and retirement decisions of older Americans; how government policies affect employers’ choices concerning employment and hours over the business cycle; the effects of financial aid on the decision to attend college; discrepancies in alternative measures of employment, wages and hours; and the measurement of economic activity. She served as Commissioner of the Bureau of Labor Statistics from 1993 through 2001 and as a Member of the President’s Council of Economic Advisers from 2011 through 2013. Abraham currently serves on standing academic advisory committees convened by the Congressional Budget Office, Bureau of Economic Analysis, and Federal Reserve Bank of Chicago. She is a Research Associate of the National Bureau of Economic Research and a Research Fellow of the IZA, a member of the American Academy of Arts and Sciences, a Distinguished Fellow of the American Economic Association, and an elected Fellow of the American Statistical Association and of the Society of Labor Economists. Abraham received her Ph.D. in economics from Harvard University in 1982 and her B.S. in economics from Iowa State University in 1976.
Manfred Antoni is a graduate of economics from the Friedrich Alexander University of Erlangen-Nuremberg (Diploma 2005). Since September 2005 he has been a researcher at the IAB. From October through December 2011 he was a visiting researcher at the Institute for Social and Economic Research (ISER) of the University of Essex in Colchester (UK). In 2012 he received his Doctorate from the Friedrich-Alexander University of Erlangen-Nuremberg.
Chris Antoun is an Assistant Research Professor at the College of Information Studies (iSchool) and Joint Program in Survey Methodology (JPSM) at the University of Maryland. His research focuses on using smartphones to collect population data, either through text messaging, mobile questionnaires, or apps and sensors. Before coming to UMD, he obtained his PhD in Survey Methodology from the University of Michigan and was a postdoctoral fellow at the U.S. Census Bureau. He is currently an associate editor for the Journal of Survey Statistics and Methodology and a member of the advisory board for the International Program in Survey and Data Science.
Trent D. Buskirk, PhD is the Novak Family Professor of Data Science and the Chair of the Applied Statistics and Operations Research Department at Bowling Green State University. His research interests are varied and include Mobile and Smartphone Survey Designs, methods for calibrating and weighting nonprobability samples, and in the use of machine learning methods for social and survey science design and analysis. Prior to his post at BGSU, Trent served as the Director for the Center for Survey Research at UMASS Boston and prior to that Trent was the Vice President for Statistics and Methodology at the Marketing Systems Group (MSG) and was tenured in the department of Biostatistics in the School of Public Health at Saint Louis University. Dr. Buskirk’s research has been published in leading survey, statistics and health related journals such as Field Methods, Journal of Royal Statistical Society, Social Science Computer Review, Journal of Official Statistics, Preventative Medicine, Cancer, Journal of Clinical Epidemiology, Survey Methods: Insights from the Field and Methods, Data and Analysis, Public Opinion Quarterly and the Journal of Survey Statistics and Methodology. Recently, Trent served as the President of the Midwest Association for Public Opinion Research and was the past Conference Chair for AAPOR. In 2017 Trent was named Fellow of the American Statistical Association. When Trent is not working or thinking about surveys or machine learning, you can find him playing resident prince to his two princesses or playing an action packed game of pickleball!
Dr. Brian Butler’s research and teaching focuses on developing theories and techniques to enable groups, communities, and organizations to harness the full potential of new technologies. This includes the design of online communities; the use of information technology to strengthen local food ecosystems; strategies for leveraging power and politics to support organizational transformation and reduce systemic bias; and development of alternative models to data governance. Since joining UMD in 2012 as a faculty member, Dr. Butler has also served as Director of the Master of Information Management (MIM) program, Director of the Center for the Advanced Study of Communities and Information (CASCI), Interim Dean, Senior Associate Dean, and co-Director of the UMD Social Data Science Center (SoDa).
Mario Callegaro is user experience survey researcher at Google UK, London, in the Cloud Platform User Experience team (CPUX). He works on any survey related projects within his organization. He also consults with numerous other internal teams regarding survey design, sampling, questionnaire design and online survey programming and implementation. Mario holds a M.S. and a Ph.D. in Survey Research and Methodology from the University of Nebraska, Lincoln. Prior to joining Google, Mario was working as survey research scientist for now Ipsos KnowledgePanel previously known as Knowledge Networks KnowledgePanel. Current research areas: user experience research, web survey design, smartphone surveys, survey paradata, and questionnaire design in which he has published numerous papers, book chapters and conference presentations. He published (May 2014) an edited Wiley book titled Online Panel Research: A Data Quality Perspective together with Reginald P. Baker, Jelke Bethlehem, Anja S. Göritz, Jon A. Krosnick and Paul J.. Lavrakas. Mario also completed a book titled: “Web survey methodology” with Katja Lozar-Manfreda and Vasja Vehovar from the University of Ljubljana, Slovenia, published by Sage in June 2015 which is also available as open access PDF and Epub at this Sage URL: https://study.sagepub.com/web-survey-methodology
Alexandru Cernat joined Social Statistics in July 2016. Prior to this he was a Research Associate at the National Centre for Research Methods.
An important part of his research is centred around modelling measurement error in the framework of generalized latent variables (i.e., Structural Equation Modelling, Latent Class and Item Response Theory) with a particular interest in applying these to longitudinal data.These statistical models are often used in the context of survey methodology to investigate topics such as: measurement error, non-response, mixed mode designs, longitudinal surveys, paradata, interviewer effects, surveying sensitive topics, etc.Another research area of interest is missing data and ways to correct for this. This work focuses especially on missing biomarkers in surveys and is part of the National Centre for Research Methods grant: Acounting for informative item nonresponse in biomarkers collected in longitudinal surveys (WP3).
Dr. Conrad is a survey methodologist whose recent work has focused on respondents’ understanding of survey questions. He also studies biases in respondents’ judgments about the frequency of their behaviors, the effect of automatic progress feedback on respondents’ willingness to continue filling out a questionnaire, and the decision to participate in a survey among potential respondents.
Jill A. Dever, PhD, has been engaged in innovative survey research for more than 20 years. She is recognized internationally for her contributions to sampling design, weighting and data analysis, as well as for educating others in these areas. She has worked on a variety of studies including those assessing the correlates of good health and vaccination use; therapy payment models for post-acute hospital care; drug use and retention in the U.S. military; smoking cessation programs; and the influence of education and family on career paths. Her research expertise includes development of software for optimizing complex sample designs; construction of analysis weights with adjustments obtained from other surveys; creation of variance estimators for complex statistics; and the evaluation of statistical and quality issues for surveys, particularly those without a defined probabilistic structure (“non-probability samples”).
Jörg Drechsler studied the piano at the Conservatory of Music Augsburg-Nuremberg from 1999 to 2003 and business administration from 2001 to 2006 at the University of Erlangen-Nuremberg. He joined the IAB in 2006. Dr. Drechsler received his PhD in Social Science from the University in Bamberg in 2009 and his Habilitation in Statistics from the Ludwig-Maximilians-Universität in Munich in 2015. He is also an adjunct assistant professor in the Joint Program in Survey Methodology at the University of Maryland.
Thomas Fetzer joined the department in 2009. He received his Ph D from the European University Institute in Florence (Department of History and Civilization) in 2005. Before joining CEU, Thomas held post-doctoral research and teaching positions at the Max-Planck Institut für Gesellschaftsforschung in Cologne (2006), the London School of Economics (2007-2008) and the University of Warwick (2009).
His current research interests are primarily related to the role of ideas in the international political economy, with a specific focus on (economic) nationalism, as well as the impact of economic globalization on socioeconomic inequality and processes of collective interest formation. In a recent project, Thomas has also explored the emergence of various notions of ‘economic Europeannness’. Beyond his own research, Thomas is interested in a number of other fields, including the comparative political economy of labour and industrial relations, EU social policy and the European social model, the history and contemporary development of multinational firms, the politics of consumption, as well as the broader area of contemporary European and transnational history, in particular with regard to issues of collective memory and identity. He also has a strong interest in the methodological debates about the relationship between history and the social sciences.
Robert Fay, Ph.D., has 40 years of experience in multiple aspects of sample surveys, including survey design, estimation, variance estimation, imputation and analysis of missing data, statistical modeling of data from complex samples, and small area estimation. He joined Westat, after retiring from the U.S. Census Bureau.
Dr. Fay is a Fellow of the American Statistical Association, a Fellow of the American Association for the Advancement of Science, and a recipient of the Gold Medal Award from the Department of Commerce and the Roger Herriot Award for Innovation in Federal Statistics. In recognition of his contributions to the field, Dr. Fay has been named a Westat Senior Statistical Fellow and serves on the Statistical Fellows Committee, which provides consultation on important survey statistics issues and addresses recent advances in applied statistics. Dr. Fay is a research professor in the Joint Program in Survey Methodology at the University of Maryland.
Babak Fotouhi joined the UMD iSchool in January 2020 as an assistant professor in computational social science. Dr. Fotouhi investigates how the structure of societal networks affect different social processes, such as pro-social behavior, and how we can utilize this knowledge towards better social outcomes. Approaching his work from a mathematical and computational perspective, he worked on modeling social dynamics at Harvard University, and subsequently at the Human Nature Lab at the Yale Institute for Network Science. Besides the relation between social networks and behavior, his research includes the computational study of historical evolution of culture and meanings, and the social construction of unquestioned assumptions. Dr. Fotouhi’s research has been published in Nature, Nature Human Behavior, Network Science, and Physical Review, among others.
For ambitious researchers, winning prestigious grants can be career making, but a growing disparity in funding awarded to men compared to women provides another obstacle for women in science. Dr. Oliveira is interested in quantifying diversity, equality and inclusion in different fields of science, and understanding the mechanics behind the diffusion of low and high quality information in online social networks. Dr. Oliveira has published several works on these topics and has been covered in major news outlets, including the New York Times, Reuters, the Huffington Post, the Smithsonian to cite a few. At the College of Information Studies, he will be working with faculty and researchers at the Social Data Science Center (SoDa) to address the unique challenges of working with social and behavioral data at ever increasing scales. Additional roles Dr. Oliveira held prior to UMD include Research Scientist at the Rensselaer Polytechnic institute/Army Research Lab, and a Postdoctoral Fellow at Northwestern and Indiana Universities.
Dr. Frias-Martinez’s research focuses on the use of large-scale ubiquitous data to model the interplay between human mobility patterns and the built environment. She is also interested in how such models can be used to aid decision makers in areas such as poverty, natural disasters or smart cities.
Dr. Gard is an Assistant Professor of Developmental Psychology, Faculty Affiliate in the Program in Neuroscience and Cognitive Neuroscience (NACS), Social Data Science Center, and the Maryland Population Research Center, and Director of the Growth And Resilience across Development (GARD) Lab at the University of Maryland, College Park. Together with her students and collaborators, she studies how environmental adversity and promotive factors shape children’s brain and behavioral development – with a particular focus on how features of the neighborhood context and the parent-child relationship guide risk and resilience processes. A prominent feature of her work is to increase sociodemographic diversity in neurobiological research by including historically under-represented groups in research design and implementation.
Thomas Gautschi holds the Chair in Sociological Methodology since Fall Semester 2009. His main research interests combine formal theory (rational choice, game theory, networks) with laboratory experiments to better understand the formation and maintenance of trust or the formation and transformation of exchange networks. He is also interested in methodological questions (statistical models) and survey research (e.g., effects of distorted sex-ratios in Germany). In general, his research is located in economic sociology.
Thomas Gautschi currently is the speaker of the School of Sociology as well as the Dean of Student Affairs at the School of Social Sciences. He also is the speaker of the DGS (Deutsche Gesellschaft für Soziologie) section on Model Building and Simulation. He previously held positions at the University of Bern, Utrecht University, and the University of Eindhoven.
Emily Geisen is a Senior Experience Management Scientist at Qualtrics. She specializes in designing user-friendly survey instruments to improve data quality and reduce respondent burden. Prior to Qualtrics, she spent 15 years at RTI International where she managed RTI’s cognitive/usability laboratory. She received her MS in Survey Methodology from the University of Michigan in 2004. She has 16 years of experience designing methodological research studies, developing and evaluating survey instruments, leading data collection tasks, managing projects, and performing statistical analyses using SAS. She is lead author of a 2017 book titled Usability Testing for Survey Research, published by Morgan Kaufmann. She was the 2017-2019 American Association for Public Opinion Research Membership and Chapter Relations chair, the 2010 conference chair for the Southern Association for Public Opinion Research (SAPOR), and the 2009–2011 secretary of the Survey Research Methods Section of the American Statistical Association. Geisen is one of the instructors for the required CSS course titled Questionnaire Design. She also teaches short courses on Usability Testing for Survey research through the Odum Institute.
Steven G. Heeringa is a Senior Research Scientist at the University of Michigan Institute for Social Research (ISR). He is a member of the Faculty of the University of Michigan Program in Survey Methods and the Joint Program in Survey Methodology. He is a Fellow of the American Statistical Association and elected member of the International Statistical Institute. He is the author of many publications on statistical design and sampling methods for research in the fields of public health and the social sciences. He is the lead author of Applied Survey Data Analysis (Chapman & Hall, 2010), a comprehensive new text on methods for the statistical analysis of complex sample survey data. Steve has over 37 years of statistical sampling experience in the development of the SRC National Sample design, as well as research designs for ISR’s major longitudinal and cross-sectional survey programs. Since 1985 Steve has collaborated extensively with scientific colleagues in the design and conduct of major studies in aging, psychiatric epidemiology and physical and mental health. He has been a teacher of survey sampling and statistical methods to U.S. and international students and has served as a sample design consultant to a wide variety of international research programs based in countries such as Russia, the Ukraine, Uzbekistan, Kazakhstan, India, Nepal, China, Egypt, Iran, the United Arab Emirates, Qatar, South Africa and Chile.
Katherine (Kate) oversees the iSchool’s five degree programs and overall curriculum. During Kate’s tenure, the College has generated and maintained a 300% increase in its student body and doubled its academic staff. Kate is applying her broad experience in educational policy and academic administration to the development of new degree programs in innovative areas of information science, including information design, social data science, gaming and media analytics, data journalism, library leadership, and smart and connected communities. Kate also teaches in the College and holds a faculty affiliation with the UMD Department of Anthropology. Her teaching and research interests focus on the study of disasters and community resilience, and she has further teaching interests in pedagogy and instructional design.
Prior to joining the UMD iSchool, Kate served as UMD’s Undergraduate and Graduate Director for Terrorism Studies and as the Education Director for UMD’s National Consortium for the Study of Terrorism and Responses to Terrorism. She has also held positions with UMD’s College of Behavioral and Social Sciences and Center for the Advanced Study of Language (CASL). She has over 15 years of experience in teaching and research in interdisciplinary social sciences.
I am Professor of Statistics and Methodology (interim) in the Department of Sociology at the University of Mannheim and Adjunct Assistant Professor in the Joint Program in Survey Methodology (JPSM) at the University of Maryland. I am affiliated with the Mannheim Centre for European Social Research (MZES), the Collaborative Research Center SFB884 “Political Economy of Reforms”, and the Mannheim Center for Data Science, as well as the Social Data Science Center (SoDa) at the University of Maryland. I am currently the Academic Director of the Mannheim Master of Applied Data Science & Measurement.
I received my PhD in Social and Economic Sciences (Dr.rer.soc.oec.) from WU, Vienna University of Economics and Business, Austria, in 2011. Before joining the University of Mannheim and JPSM, I was Senior Researcher at the International Program in Survey and Data Science and Post-doctoral Research Fellow at the Program in Survey Methodology at the University of Michigan’s Institute for Social Research.
In my research, I develop, implement, and assess modern methods of collecting data for the behavioral and social sciences. In particular, I am interested in how to jointly collect self-reports (usually via (mobile) web surveys) and passive measurement from smartphone and wearable sensors, online and device log files, Internet search queries, and other digital traces to better study research questions on migration, employment, and inequality. Feel free to browse through my publications and contact me if you are interested in collaborating or if you do have any questions.
Brian Kim is an Assistant Research Professor in the Joint Program in Survey Methodology and a Co-director for the Social Data Science Major at the University of Maryland. He received his PhD in Statistics from the University of California, Los Angeles. His research focuses on social network analysis, network sampling methods (particularly respondent-driven sampling), and population size estimation.
Professor Frauke Kreuter is Co-Director of the Social Data Science Center and faculty member in the Joint Program in Survey Methodology at the University of Maryland, USA; and Professor of Statistics and Data Science at the Ludwig-Maximilians-University of Munich. She is an elected fellow of the American Statistical Association and the 2020 recipient of the Warren Mitofsky Innovators Award of the American Association for Public Opinion Research. In addition to her academic work Dr. Kreuter is the Founder of the International Program for Survey and Data Science, developed in response to the increasing demand from researchers and practitioners for the appropriate methods and right tools to face a changing data environment; Co-Founder of the Coleridge Initiative, whose goal is to accelerate data-driven research and policy around human beings and their interactions for program management, policy development, and scholarly purposes by enabling efficient, effective, and secure access to sensitive data about society and the economy. coleridgeinitiative.org; and Co-Founder of the German language podcast Dig Deep.
Eun Kyoung Choe is an Associate Professor and Doctoral Program Director in the College of Information Studies at the University of Maryland, College Park. Her research bridges the fields of Human-Computer Interaction (HCI), Health Informatics, and Ubiquitous Computing. With an overarching goal of empowering individuals, her research centers on examining major challenges people face in leveraging personal data, such as personal data collection and exploration. More recently, she has been exploring multimodal interaction as a means to collect rich personal data, promote reflection, and help people dive into their data. Her work has been funded by the National Science Foundation, National Institutes of Health, and Microsoft Research. She has been serving on the editorial boards of PACM IMWUT and Foundations and Trends in Human-Computer Interaction. She received her Ph.D. in Information Science from the University of Washington.
Partha Lahiri is a Professor in the Joint Program in Survey Methodology (JPSM) and in the Department of Mathematics at the University of Maryland, College Park and an Adjunct Research Professor of the Institute of Social Research, University of Michigan, Ann Arbor. Prior to joining the University of Maryland, College Park in 2002, he held an appointment as the Milton Mohr Distinguished Professor of Statistics at the University of Nebraska-Lincoln. He has served on a number of advisory committees and panels, including the U.S. Census Advisory committee and U.S. National Academy of Sciences panel. Over the years he advised various local and international organizations such as the United Nations Development Program, World Bank, and the Gallup Organization. He has been an associate editor of Survey Methodology and the Journal of the American Statistical Association. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics and an elected member of the International Statistical Institute.
James Lepkowski is a survey methodologist at the Institute for Social Research where he directs the Summer Institute in Survey Research Techniques. He has been on the faculty of Biostatistics and the Institute for Social Research since 1982, conducting research on survey sampling and estimation as well as teaching courses on sampling, surveys, and related topics.
Dr. Yan Li is interested in combining her background in computer sciences, genetic and survey methodology with her research experience with National Cancer Institute to develop statistical methods for efficiently designing and analyzing complex samples in a biomedical setting. Particularly, her interests include improving population representativeness of nonprobability samples, health disparity analyses, genetic association using case-control, cohort and cross-sectional studies and surveys with complex designs.
Recognized worldwide as an information management industry thought leader, David has popularized best practices for business intelligence, data governance, performance computing, master data management, predictive analytics, and data quality.
David is a monthly columnist for TechTarget and is a frequent presenter at The Data Warehousing Institute World Conferences, Enterprise Data World, the Data Governance and Information Quality conferences, as well as web-based seminars. In addition, he has published several books and dozens of white papers on practical issues for information management.
I am an assistant professor of data science and public policy at the Hertie School in Berlin. My research focuses on public opinion, attitude formation in the digital age, and the use of online data in social research. I use experimental methods, online data, and innovative measurement strategies to study how people act and think, politically. Find my CV here.
Raphael Nishimura is the Director of Sampling Operations in Survey Research Operations. He has been working with sampling and survey statistics for over ten years. He holds a PhD in survey methodology from the University of Michigan and a bachelor’s degree in statistics from the University of SÃ£o Paulo. His main research interest includes sampling methods, survey nonresponse and adaptive/responsive designs. He is also the director of the Sampling Program for Survey Statisticians of the SRC Summer Institute for Survey Research Techniques.
Sarah Oates is a scholar in the field of political communication and democratization. A major theme in her work is the way in which the traditional media and the internet can support or subvert democracy in places as diverse as Russia, the United States and the United Kingdom. Oates also is the research director for the college and an affiliate professor in the UMD Department of Communication.
Oates has published many books, articles, chapters and papers on topics including how the internet can challenge dictatorship, how election coverage varies in different countries and how national media systems cover terrorism in distinctive ways. One of her most recent books, “Revolution Stalled: The Political Limits of the Internet in the Post-Soviet Sphere” (Oxford University Press), found faint hope for online mobilization in Russia. She teaches undergraduates, graduates and supervises doctoral dissertations in digital politics, political communication and journalistic norms. Her current work examines how political messages travel through media ecosystems, analyzing why some stories gain more attention than others from audiences. This includes work on how Donald Trump gained huge public attention via the media in the 2016 election. Click here to download.
Before embarking on her academic career, Oates was a journalist who published in outlets ranging from the Orlando Sentinel to The New York Times. She has lived, studied and worked in Scotland and Russia. You can view more about her work and download selected work at www.media-politics.com. You can follow her on Twitter @media_politics. She frequently comments on politics for the BBC.
Daniel Oberski external linkis an Associate Professor in Data Science, Methodology and Statistics. He obtained his PhD in Tilburg and has already been a visiting professor in Maryland. In 2014, he received a Veni grant for research into the question how human behaviour can be measured with scientific research.
I am broadly interested in characterizing spatial patterns and processes through the use of quantitative geographic methods, which typically falls under the banners of spatial analysis and spatial statistics, geographic information science, and the emerging discipline of spatial data science. My work typically involves modeling human processes within urban environments and therefore also intersects with the disciplines of computational social science, and urban informatics. Overall, my research has targeted the development of multivariate spatial statistics and how they can be used to capture how relationships change by spatial and temporal contexts. This includes issues of theory, interpretation, scalability, and integration of traditional geographic models with novel “big” datasets, as well as applications in public health, crime, urban mobility, and transportation systems. I also participate in open source software development and building cyber-infrastructure to support my research and teaching and facilitate the replicability and reproducibility of the geographical science
Susannah Paletz received her PhD in social/personality psychology from the University of California, Berkeley. In early 2004 she joined NASA Ames Research Center as a civil servant Research Psychologist, first in the Distributed Team Decision Making Laboratory (2004-2006) and then in the Human-Computer Interaction (HCI) Group (2006-2008). From 2008 to 2013, Paletz was grant-funded at the University of Pittsburgh, where she studied social and cognitive aspects of team processes. Paletz joined the University of Maryland Center for Advanced Study of Language (CASL) as an Associate Research Scientist in 2013 (promoted to Research Scientist in 2017). She joined the iSchool as a Research Professor in 2019, and in 2021 became an Associate Professor. She uses a variety of research methods, analyzing data from surveys, experiments, interviews, archives, social media, audio, and video.
Dr. Patra’s research looks at the interface of science, technology, and society. She is well equipped to take any science and technology and see the impact of that particular technology on society and vice versa. She has the expertise and ability to explore the broader issues associated with technologies such as biotechnology, nanotechnology, food technology, environmental technology, emerging technologies, and its impact on society. She has worked on several social issues such as policy, risk perception and communication, ethics, health, in the context of nanotechnology in the developing countries. Currently her research is focused on social issues associated with stormwater management across urban ecosystems.
Philip Piety is a Learning Scientist who supports undergraduate and graduate programs through teaching and research. He began at the iSchool in 2014 and has also taught at the Smith School of Business at Maryland and Johns Hopkins School of Education. After a career in the technology field with Oracle and IBM, he returned to college as an adult to earn a BS in Information Systems and Computer Science from the University of Maryland’s University College.
Some of the courses he teaches involve technology infrastructures and architecture as well as organizations, management, and teamwork. He also works with and has written about educational data technologies and learning analytics/education data science. He is the director of the Maryland Education Digital Infrastructures and Analytics Lab. He is a strong proponent of project-based learning and using methods to develop unique projects with his students.
Stanley Presser is interested in the interface between social psychology and survey measurement. His research focuses on questionnaire design and testing, the accuracy of survey responses, nonresponse, and ethical issues stemming from the use of human subjects. His books include Questions and Answers in Attitude Surveys (with Howard Schuman), Survey Questions (with Jean Converse), and Methods for Testing and Evaluating Survey Questionnaires (chief editor). In addition to being professor of sociology, he teaches in the Joint Program in Survey Methodology, which he founded in 1992 with colleagues at the University of Michigan and Westat, Inc. He has served as editor of Public Opinion Quarterly, was president of the American Association for Public Opinion Research, and is an elected fellow of the American Statistical Association. Presser was director of the Maryland Survey Research Center from 1989 to 2000.
Louiqa Raschid is a professor at the University of Maryland where she holds appointments in the Smith School of Business, theInstitute of Advanced Computer Studies (UMIACS) and the Department of Computer Science. She is a member of the Computational Linguistics and Information Processing (CLIP) Lab, the Database Group and the Center for Bioinformatics and Computational Biology.
She has over two decades of experience in data science, a computational paradigm with the potential to fundamentally change the way we exploit data driven decision making to support a broad range of human activities. Raschid has made pioneering contributions towards meeting data integration, data management and data mining challenges in multiple non-traditional domains. Her multidisciplinary research spans the fields of computer science to business information systems, with a strong link to important data science applications including the life sciences and health sciences, humanitarian disaster relief applications, human behavior modeling within social streams, and the modeling and management of financial ecosystems. She has been an ACM Distinguished Scientist since 2008 and was named an ACM Fellow in 2016.
Jen is a Staff UX Researcher and Manager at Google, an instructor at UC Berkeley Extension, an instructor at the University of Maryland, and a UXR Coach. She specializes in efficient applications of research methods to ensure scientific rigor is not compromised while working fast to gain actionable results. Jen’s research specialties include usability, eye tracking, survey design, experimental design, and cognitive aging. Jen is an established expert in the field – she teaches graduate-level classes, trains UX professionals, and coaches people who are entering the field. She is co-author of Usability Testing for Survey Research (2017) and co-author/editor of Eye Tracking in User Experience Design (2014). She has held UX positions in both industry (Facebook, Instagram, Bridgewater Associates, Principles by Ray Dalio, Fors Marsh Group) and government (US Census Bureau), and has worked as an independent consultant as well.
Jen is an established leader in the UX field: she is the founder of the mentorship program, webinar program, and short course program for the User Experience Professional Association (UXPA) and is a Board Member of the UX Quality Certification Center (UXQCC). She is the founder of the Research Challenge Workshop and is expanding her coaching business to include a network of coaches. She is past President of the UXPA, past President of the DC chapter of UXPA, past President of DC chapter of the American Association of Public Opinion Research (AAPOR), and past Director of Marketing and Communications for the UXPA, and past Membership Chair for the Pacific chapter of AAPOR (PAPOR). Jen received a Ph.D. in Applied/Experimental Psychology from Catholic University of America.
Joseph Sakshaug is distinguished researcher, deputy head of research, and head of the Data Collection and Data Integration Unit in the Statistical Methods Research Department at the IAB. He is also university professor of statistics at the School of Mathematics, Computer Science, and Statistics at the LMU Munich (Ludwig-Maximilians-Universität München) and honorary full professor at the School of Social Sciences at the University of Mannheim. Previously, he was associate professor (senior lecturer) in Social Statistics at the University of Manchester (UK), and assistant professor (junior professor) of Statistics and Social Science Methodology at the University of Mannheim (Germany). Mr Sakshaug received his MSc and PhD in Survey Methodology from the University of Michigan-Ann Arbor, and his BA in Mathematics from the University of Washington-Seattle. From 2011 to 2013, he was an Alexander von Humboldt postdoctoral research fellow at the IAB and the LMU Munich. He is also a faculty member in the International Program in Survey and Data Science, and an adjunct research assistant professor at the Survey Research Center of the Institute for Social Research at the University of Michigan. His research focuses on data quality issues in complex surveys, the integration of multiple data sources, and empirical research methods.
Dr. Sharan Sharma is an Assistant Research Professor with appointments in the departments of Sociology and the Joint Program in Survey Methodology. His research interests include cross-cultural methodology, interviewer effects, interviewer-respondent interaction, survey falsification, paradata, and modeling complex survey data. His management interests lie in the planning and implementation of large-scale complex surveys; more specifically, in organization development, capacity and capability building in developing countries, and process management.
Dr. Sharma has close to two decades of experience in the private sector, most recently as Senior Vice President for TAM India (a Kantar-Nielsen joint venture) where he held responsibilities spanning research, business development, and corporate affairs.
Katie Shilton is an associate professor in the College of Information Studies at the University of Maryland, College Park, and leads the Ethics & Values in Design (EViD) Lab. Her research explores ethics and policy for the design of information technologies. She is the PI of the PERVADE project, a multi-campus collaboration focused on big data research ethics. Other projects include developing privacy-sensitive search for email collections; analyzing ethical cultures in computer security research; and building tools to facilitate ethics discussions in mobile application development.
Dr. Sivan-Sevilla is a comparative social scientist & technologist who measures and theorizes about the way our information society is governed. He investigates digital risk governance over a broad range of cybersecurity, privacy, discrimination, and manipulation problems, looking at governance structures set by private industries, elected officials, and bureaucrats, across sectors and political systems. Methodologically, Ido utilizes his technological background to empirically investigate industries (e.g. AdTech) and threat actors (e.g. hackers & trackers), shedding light on bottom-up governance arrangements. He complements such understanding with text analysis, interviews, and surveys to uncover and explain the operation of top-down policy regimes in this space, by private and public actors (e.g. cyber insurers, certifiers, policymakers, and regulators).
His work has been published or presented in The Journal of Public Policy, Journal of Risk Research, Policy & Internet, Georgetown Journal of International Affairs, NATO’s International Conference on Cyber Conflict (CyCon), and FTC’s Privacy Conference, among other venues.
Dr Stapleton is interested in the analysis of administrative data and survey data obtained under complex sampling designs, multilevel latent variable models, tests of mediation within a multilevel framework
Kathleen Stewart is Professor in the Department of Geographical Sciences and Director of the Center for Geospatial Information Science. She works in the area of geographic information science with a particular focus on geospatial dynamics. She is interested in mobility and spatial access, often in a big geospatial data context and using approaches that lie in the expanding field of spatial data science. She investigates movement and mobility for a number of different application domains, for example, health and transportation where movement patterns or behaviors and spatial access are key topics. She is also interested in modeling geospatial semantics including geospatial ontologies and their role for location-based applications, and spatiotemporal information retrieval, i.e., computational methods for automatically acquiring meaningful space-time information from text sources. She teaches in the areas of spatiotemporal data modeling, geographic database design, geovisualization and cartography, and fundamentals of geographic information science. At the University of Maryland, Dr. Stewart is a member of the Program in Oncology at the University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center and also collaborates with researchers at the Center for Vaccine Development and Global Health, the Center for Substance Abuse Research, the Maryland Transportation Institute, the School of Public Health, and the Social Data Science Center among others. Her research is supported in part by grants from the National Institutes of Health, the National Science Foundation, the Federal Highway Administration, and Maryland Department of Natural Resources among other organizations.
Dr Sweet is interested in social network analysis, Network interference, Bayesian statistics, statistical modeling, data science, machine learning
I am a Professor of Political Science and Empirical Democracy Research in the School of Social Sciences at the University of Mannheim. I am also affiliated with the Institute of Empirical-Analytical Research (InFER) and the Research Institute Social Cohesion (RISC) at Goethe University Frankfurt. Previously, I held positions at the Graduate School of Economics and Social Sciences (GESS) in Mannheim, Goethe University Frankfurt, the University of Essex, the Mannheim Centre for European Social Research (MZES) as well as the universities of Berne and Konstanz. I study the socio-structural and psycho-cultural requisites of democracy with a strong focus on problems of social cohesion and conflict. My current research involves the politics of free speech and censorship, citizens’ preferences for migration policy, the rural-urban political divide and the civic consequences of wartime sexual violence. I also have a keen interest in quantitative political methodology, including Bayesian methods, data visualization and survey experiments. My work has been published in British Journal of Political Science, Comparative Political Studies, Political Analysis, and Sociological Methods & Research, among others.
Richard Valliant received a PhD in biostatistics from Johns Hopkins University. His current research interests include the use of models in survey estimation, sample design problems, and analysis of complex survey data. He has over 35 years of practical survey experience, including work on the Consumer Price Index, Producer Price Index, and other surveys that supply some of the nation’s important economic indicators. He is a fellow of the American Statistical Association and has served on the editorial boards of three statistical journals.
Jessica Vitak is an associate professor in the College of Information Studies and an affiliate professor in the Communication Department at the University of Maryland. Her research evaluates the privacy and ethical implications of big data, the internet of things, and other “smart” technologies. She seeks to understand how privacy concerns play a role in technology adoption and use, and she develops tools and resources to help children and adults make more informed decisions when using technology and sharing sensitive data.
Dr. Winter studies the co-evolution of technology and work practices, and the organization of work. She has recently focused on ethical issues surrounding civic technologies and smart cities, the social and organizational challenges of data reuse, and collaboration among information workers and scientists acting within highly institutionalized sociotechnical systems. She has published over 70 refereed articles in journals, conference proceedings, and edited books. Her work has been supported by the U.S. National Science Foundation and by the Institute of Museum and Library Services. She was previously a Science Advisor in the Directorate for Social Behavioral and Economic Sciences, a Program Director, and Acting Deputy Director of the Office of Cyberinfrastructure at the National Science Foundation supporting distributed, interdisciplinary scientific collaboration for complex data-driven and computational science. She received her PhD from the University of Arizona, her MA from the Claremont Graduate University, and her BA from the University of California, Berkeley.
Ting Yan is a Research Assistant Professor in the Survey Methodology Program. She received her Ph.D. from the Joint Program in Survey Methodology in 2005. She completed her post-doctoral training at the Institute for Social Research, University of Michigan. She had worked at NORC at the University of Chicago as a Senior Survey Methodologist before joining the Survey Methodology Program.
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