The Carlson School is consistently ranked among the nation's top five programs for management information systems. Widely recognized as pioneers in the field, the Carlson School's Information and Decision Sciences faculty develop and teach the majority of the MSBA curriculum.
Working with MSBA Faculty
Students reflect on the passion and energy Carlson School faculty bring to the classroom and the MSBA program.
MSBA students learn directly from these and other scholars at the Carlson School:
Gediminas Adomavicius studies computational techniques for aiding decision-making in information-intensive environments. He is an expert in personalization technologies, data mining, and electronic market mechanisms. His current research examines next-generation recommender systems. Professor Adomavicius received the National Science Foundation CAREER award in 2006 for his research on personalization technologies.
Ravi Bapna teaches graduate students, executives, CIOs, and CMOs how to leverage the digital revolution for competitive advantage. His research interests include the economics of information systems, peer influence in online social networks, freemium business models, and the Internet as a new kind of "lab" for research into fundamental human constructs like trust, altruism, reputation, and decision-making. Dr. Bapna is the academic director of the MS in Business Analytics program at the Carlson School.
Gord Burtch researches the economic evaluation of information systems, with a focus on individual behavior in online social contexts. His work often uses large-scale web data to identify and quantify behaviors. Professor Burtch is an expert in user behavior on crowdfunding and crowdsourcing platforms. Media outlets, including Forbes and the Wall Street Journal's Marketwatch, have reported on his work.
Jason Chan advises student teams in the completion of data analytics projects for partner companies in the Carlson Analytics Lab. Professor Chan uses a variety of quantitative methods including econometric modeling, experiments, and technical methods, to extract meaningful relationships from within datasets. His research examines the intersections of Internet platforms and social outcomes related to healthcare, crime, financial well-being, education, and labor discrimination.
Shawn Curley joined the Carlson School in 1986 after completing an MA in mathematics and a PhD in psychology from the University of Michigan, Ann Arbor. His research interests are in individual decision-making. Of particular interest is the role of uncertainty in decision-making -- how we can capture individuals' judgments of uncertainty, how we can evaluate the quality of such judgments, and how uncertainty does and should impact our decisions. His teaching interests include the use of desktop technology to support decision-making, and the application of psychological and decision theory to the practice of management.
Alok Gupta is a widely recognized expert in the field of management information systems, and the economics of electronic commerce in particular. He has been awarded a prestigious NSF CAREER Award and named an INFORMS ISS Distinguished Academic Fellow in addition to being widely published. Professor Gupta co-designed the MSBA curriculum and currently serves as the associate dean for faculty and research at the Carlson School of Management.
De Liu teaches students how to combine large-scale data harvesting and deep analysis to derive insights about markets and user behaviors. He applies these techniques to digital advertising, peer-to-peer markets, and gamification in education and healthcare. He received best reviewer and best associate editor awards from Information Systems Research and holds editorial roles at other top academic journals.
Svjetlana Madzar teaches on topics related to leadership and teamwork. She is particularly interested in structures and processes of teams that span international borders and cultures, as well as the impact of technologies on team performance.
Edward McFowland is a data and computational social scientist. He specializes in computationally efficient algorithms for large-scale statistical machine learning and big data analytics. His research bridges the gap between machine learning and social sciences (e.g., economics, public policy, and management) to inform public policy and address real world problems faced by organizations and society more broadly.
Ken Reiley is an instructor of information and computer science. He also provides consulting services in software research, development, and architecture; process development; and training and education. His experience includes senior technical and engineering roles at 3M, Cargill, and Microsoft, where he contributed to the original .NET platform. Reiley has published academic papers on tracking, mapping, mobile applications, and computer science education.
Maria Ana Vitorino applies statistics and economic models of industrial organization to marketing. Her research interests include firms' pricing strategy, consumer-choice models, and using game-theoretic models to explain the strategic impact of firms' entry decisions.