Faculty research groups
These groups focus on specific research outcomes within the information science field, and are led by UMSI faculty.
The Community Health Informatics Lab focuses on the potential of information systems and services to improve the health and well-being of groups that experience disease-related health disparities. The lab investigates technology-enhanced disease prevention, management, care and support in everyday life contexts, as well as at the interface of clinical and community-based care. UMSI lead is Tiffany Veinot.
The CLAIR (computational linguistics and information retrieval) research group focuses on text analysis, natural language processing, information retrieval and network analysis. UMSI lead is Dragomir Radev.
Scholars in the field of information and communication technologies and development (ICTD) seek to do two things: understand how the world's underserved communities interact with digital technology; and design new technologies, systems, and processes to support socio-economic development. Members of the ICTD group at UMSI conduct research on the sharing economy, lower-income livelihood opportunities, technology and religious institutions, aspirational theories of development, social media in political discourse, and accessibility in the developing world, among other things. We do work in the metropolitan Detroit area as well as in international contexts.
Archival and information science theories and methods hold abiding value for exploring knowledge-intensive aspects of society, such as cultural heritage (libraries, archives, and museums), academic scholarship, government, health, and education. Our interdisciplinary research group investigates complex socio-technical problems related to information and data curation, access, use, and discovery employing a range of qualitative and quantitative research methods.
The Information Behavior and Interaction Research Group focuses on examining how people interact with information during the process of information seeking, evaluation and use. We study information-related behavior and human interaction with information in various contexts including everyday life information seeking, work environments and learning situations. UMSI lead is Soo Young Rieh.
The Interaction Ecologies Group seeks to understand the embedded, interconnected nature of emerging forms of the ways people interact with computers and to build tools that help people understand, manage and make use of the rich and dynamic resources available to them. UMSI lead is Mark Newman.
The Learning, Education, and Design (LED) Lab is a community of scholars whose shared goal is to investigate how instructional technologies and digital media are used to innovate teaching, learning, and collaboration. Members of the lab come from several programs at Michigan, including information, education, psychology, survey research and the professional schools (e.g., medical education). The LED Lab is committed to providing a significant contribution to scholarship about learning at Michigan and in the broader field as well by building an empirical evidentiary base for the design and support of technology-rich learning environments. UMSI lead is Stephanie Teasley.
Michigan Autonomous Vehicle Research Intergroup Collaboration (MAVRIC) is a cross-campus multidisciplinary collaboration to study Autonomous Vehicles at the University of Michigan. MAVRIC represents a truly multidisciplinary approach to studying Autonomous Vehicles. Members of MAVRIC are from the School of Information, Department of Industrial and Operations Engineering, Department of Mechanical Engineering and the University of Michigan's Transportation Research Institute. MAVRIC's research has been sponsored by the U.S. Army Tank Automotive Research, Development and Engineering Center (TARDEC), Toyota Research Institute (TRI), MCity/Mobility Transformation Center.
Over the last several years, the research community at the University of Michigan focused on mining large amounts of data (whether structured, semi-structured, textual or multimedia) has grown significantly. MIDAS group members are interested in developing new data mining techniques and are now hosted in several units, including computer science and engineering, information, statistics, linguistics, and mathematic, and also several domain units in the natural sciences, medical sciences, social sciences and humanities, with faculty interested in the use of data mining techniques to advance science in their domain. UMSI lead is Dragomir Radev.
Michigan Interactive and Social Computing (MISC) connects researchers studying human-computer interaction, social computing and computer-supported cooperative work across the University of Michigan.
Funded by the National Science Foundation, Open Data allows fellows to engage in a vibrant set of research activities in the conduct of responsible data-intensive science and engineering involving faculty and PhD students from the School of Information, Computer Science and Engineering, Bioinformatics, Materials Science, and Chemical Engineering. Open Data is designed to build a new community of practice around open sharing and reuse of scientific data. UMSI lead is Margaret Hedstrom.
The Social Media Research Lab (SMRL) explores the effects of social media use in home, school, and work settings. We draw on theories from computer-mediated communication, media studies, online communities, and human-centered computing in our research. Our goal is to understand how social media use affects everyday life and how it can be leveraged to positively impact educational outcomes, civic engagement and social relationships. UMSI leads are Nicole Ellison, Eric Gilbert, Cliff Lampe, Casey Pierce and Sarita Yardi Schoenebeck.
Social Wellness Interventions Research Group studies the integration of wellness applications with existing social network sites to create wellness interventions using social computing. UMSI lead is Paul Resnick.
The SocialWorlds research group focuses on collaborative technologies (including computer-supported cooperative work and social computing) and increasingly pervasive computing. UMSI lead is Mark Ackerman.