Meet Our Team
As Director of the Center for Business Analytics, Ahmed Abbasi plays an integral role in developing McIntire's analytics-related curriculum, fostering industry involvement, and leading the School's big data research efforts. He has over 10 years of experience pertaining to predictive analytics, with applications in e-commerce, online fraud and security, text mining, and social media. Abbasi's research has been funded through multiple grants from the National Science Foundation. He has also received the IBM Faculty Award and AWS Research Grant for his work on big data. Abbasi has published over 50 peer-reviewed articles in top journals and conferences, and has won multiple best paper awards. His work has been featured in various media outlets, including The Wall Street Journal, the Associated Press, and Fox News.
David Dobolyi is a Research Scientist at McIntire’s Center for Business Analytics. He teaches courses in business analytics and statistical programming in both the undergraduate and graduate programs. His diverse academic background spans several fields, including cognitive psychology, English literature, and computer science. His research is currently focused on predictive analytics, machine learning, online fraud prevention, text mining, and social media analysis.
Professor Kitchens conducts research regarding the use of business analytics for examining firm value and competition, as well as for data-driven decision making. His research in this area includes projects related to measuring latent constructs through text and data mining, utilizing large-scale event studies to understand the value of firm business functions, evaluating the impact of electronic markets on local geographic competition, and determining factors related to customer churn in multichannel settings.
Jingjing Li is an Assistant Professor of IT at the McIntire School of Commerce. She has over six years of research experience pertaining to machine learning and big data analytics, with applications in information extraction, text mining, social media, search and relevance, and recommendation systems. Her research has both academic recognition and industry impact. Before joining McIntire, she was a scientist at Microsoft, developing large-scale machine learning solutions for numerous Microsoft products such as Xbox, Windows 8, Windows Phone, Cortana, and Bing. She also received a teaching award for her business intelligence course at the University of Colorado at Boulder's Leeds School of Business.
Sreekanth Mallikarjun is a Visiting Scholar in McIntire’s Center for Business Analytics. A Senior Data Scientist at Reorg Research in Manhattan, he has both academic and industry experience in machine learning, natural language processing, and statistical models that leverage business data for producing actionable insights for decision making and generating revenue. He has successfully built and executed many data science models into business workflows that deal with document classification, topic modeling, sentiment analysis, churn prediction, anomaly detection, user engagement, information extraction, recommender engine, gamification, etc. He has four years of teaching experience and has published in top peer-reviewed journals in his field.
Trey Maxham links digital, mobile, and social analytics with customer survey data and basket composition purchase data to explore omnichannel customer behavior and loyalty trends over time. He also links multisource data from customers, frontline employees, and stores (or units) to help managers better understand how customer experiences shape customer loyalty over time. Maxham leverages multivariate data analysis, structural equation modeling, hierarchical linear and nonlinear modeling, and sentiment analysis to conduct field experiments in the marketplace that offer timely insights across retail, hospitality, industrial sales, and other service sectors.
Professor Netemeyer is the Ralph A. Beeton Professor of Free Enterprise at the McIntire School of Commerce. His expertise includes the advanced analytic (AA) techniques of cluster analysis, factor analysis, discriminant analysis, multiple and logistic regression, structural equation modeling, hierarchical linear modeling, and measurement and psychometrics. He uses IBM SPSS, SAS, and R statistical packages in applying these AA techniques. He currently teaches AA in the M.S. in Commerce and undergraduate Customer Analytics courses using big data sets supplied by Center for Business Analytics corporate partner Kate Spade.
As Assistant Dean of Corporate & Foundation Relations, Allison Teweles develops and maintains the relationship between the Center and the business analytics community. Teweles works with Center board member organizations to create and sustain strategic partnerships that provide value to the members and support McIntire's efforts in the business analytics area. In addition to working with Center for Analytics organizations, Teweles is responsible for establishing strategic, multilevel partnerships with corporations and foundations for support of School-wide priorities and academic programs.