Dr. Kang Zhao is an Associate Professor of Business Analytics, with a joint appointment in Informatics, at the University of Iowa. He leads the Data and Network Analytics Research Group. His current research focuses on data science and business intelligence, especially the mining, modeling, and simulation of social media, online communities, and social/business networks. He has published more than 30 journal papers with an h-index of 18. His research has been featured in public media from more than 25 countries, such as Washington Post, USA Today, Forbes, Yahoo News, New York Public Radio, BBC and Agence France-Presse. He served as the Chair for INFORMS Artificial Intelligence Section (2014-2016). He has been an associate editor for ICIS, a guest editor for IEEE Intelligent Systems, and an NSF panelist. He is currently an editor for Journal of the Association for Information Science and Technology, and a PC co-chair of INFORMS Data Science Workshop. He has been a reviewer for 30 journals and a PC member for more than 10 conferences/workshops. He was the recipient of Early Career Research Awards by Tippie College of Business and the best paper award of INFORMS Data Science Workshop 2017.
The Internet and web have revolutionized the way we interact with each other and the world around us. Despite the increasing value of Cyberspace and the huge amount of data generated by online activities, individual and organizational behaviors in the offline physical world still have significant business and societal implications. This talk will introduce my research on mining and integrating data from both online and offline sources to gain insights into such behaviors. I will cover projects on predicting reciprocal links in online social networks, identifying health outcomes from online health communities, and analyzing the role of person-organization fit in hiring decisions.