Margret Bjarnadottir is an Assistant Professor in the Operations Management and Management Science group at the Smith School of Business at the University of Maryland. Her research focuses on decision support that builds on large-scale data. Her work spans applications in people analytics, health care, finance and sports. Specifically, her analytical modeling has been applied to the eradication of demographic pay gaps, post marketing drug surveillance, cost predictions, decision support in cancer care and for opioid prescribing and in analyzing nationwide cross-ownership patterns and systemic risk in finance. Dr. Bjarnadottir has consulted and worked for a number of health care start-ups, the parliamentary appointed Special Investigation Commission into the Banking Crash in Iceland as well as the Central Bank of Iceland where she focused on capital control fraud detection.
P. K. Kannan is the Dean’s Chair in Marketing Science at the Smith School of Business at the University of Maryland. His current research focuses on digital marketing – attribution and marketing mix models in online and mobile environments, freemium models, and defining competitive market structure using online data. He has consulted for firms in different verticals spanning hospitality, online content publishers, consumer durable and analytics consultancy, mainly in the areas of attribution, mobile app engagement, and online pricing. He has won numerous prestigious awards for his marketing research. Dr. Kannan was awarded the University of Maryland’s Distinguished University Professor in 2018, the highest award given to faculty.
Liye Ma is an Associate Professor of Marketing at the Smith School of Business at the University of Maryland. His research focuses on the dynamic interactions of consumers and firms on Internet, social media and mobile platforms. He develops quantitative models to analyze the drivers of consumer actions in the digital economy, and uses the findings to help firms develop digital marketing strategies. His research is widely published in leading academic journals, and several have been finalists for academic awards in marketing research.
Michel Wedel is the Pepsico Chaired Professor of Consumer Science at the Smith School of Business at the University of Maryland. He has improved the understanding of consumer behavior and marketing decision making through the development and application of statistical and econometric methods. He is a pioneer and leading expert in methodology for response-based market segmentation, product positioning, new product development and customization, and for the analysis of eye movements to improve visual marketing, including advertising, packaging, shelf and website design. Dr. Wedel was awarded the University of Maryland’s Distinguished University Professor in 2015, the highest award given to faculty.
Jie Zhang is a Professor of Marketing and the Harvey Sanders Fellow of Retail Management at the Smith School of Business at the University of Maryland. Her general research interest is to apply advanced data analytics techniques to study shopper behaviors and retail strategies in the digital and multichannel retail environment. She is a recognized expert in digital/Internet retailing, promotion strategies, retail management, and quantitative marketing models. Her recent research projects focus on online shopping cart abandonment, mobile app monetization strategies, online deal platforms, and loyalty programs. As an industry expert Dr. Zhang is often quoted on topics of interest in the retail and business community.
Kunpeng Zhang (KZ) is currently an Assistant Professor in the Department of Information Systems at the Smith School of Business, University of Maryland. His research interests are in the area of large-scale data analysis with particular focuses on mining social media data through machine learning/deep learning, social network analysis, computer vision, and natural language processing techniques. For example, he analyzed billions of historical temporal activities regarding user-brand interactions on Facebook to infer user interests for precise targeting and measure brand favorability. Dr. Zhang also designs algorithms to understand image memorability, complexity, and how they affect social engagement. In addition, he works on recommender systems related to trajectory, such as next POI recommendation, user correlation across platforms, etc.