麻豆传媒

P. K. Kannan is the Dean鈥檚 Chair in Marketing Science at the Robert H. Smith School of Business at the University of Maryland. His research expertise is on marketing modeling, applying statistical,  econometric, machine learning, and AI methods to marketing data. His current research stream focuses on digital marketing - mobile marketing, attribution modeling, media mix modeling, new product/service development and customer relationship management (CRM).

He has received several grants from National Science Foundation (NSF), Mellon Foundation, SAIC, and PricewaterhouseCoopers for his work in this area and research papers have been published in Marketing Science, Management Science, Journal of Marketing Research, Journal of Marketing, and International Journal of Research in Marketing. His research has also won the prestigious John Little Best Paper Award (2008) and the INFORMS Society for Marketing Science Practice Prize Award (2007). His research has also been selected as a finalist for the Paul Green Award twice (2008, 2014) and he has won the AMA/MSI Paul Root Award twice (2014, 2016).

Dr. Kannan is the Editor-in-Chief of the International Journal of Research in Marketing, an Associate Editor for Journal of Marketing Research, and serves on the editorial boards of Marketing Science, Journal of Marketing, Journal of Service Research. Dr. Kannan has served as the Chair for the American Marketing Association SIG on Marketing Research and has chaired the INFORMS Service Science section.

His teaching interests include marketing modeling, digital marketing, customer relationship management, and pricing. He has taught these courses in executive programs for Black & Decker, Home Depot, ARINC, McCormick, and Northrup Grumman. He has corporate experience with Tata Engineering and Ingersoll-Rand and has consulted for companies such as Frito-Lay, Pepsi Co, Giant Food, Black and Decker, SAIC, Fannie Mae, and IBM.

Gaurav Jain, an assistant professor of marketing at the Rensselaer Lally School of Management, examines how individuals make judgments, estimates, and decisions in the absence of complete information. Prior to earning his Ph.D. from the Tippie College of Business at the University of Iowa, Gaurav earned his bachelor鈥檚 degree in engineering and an MBA in marketing. More specifically, his research spans the fields of numerical cognition and judgment, working memory capacity, and, attention limitations. Using psycho-physical methods, such as eye tracking and facial expression analysis, Gaurav makes novel predictions about how various cognitive biases influence consumer choices.