Topic: Navigating the Frontier: Unstructured Data and the Future of AI

Speaker: Xin Wang, Virginia Polytechnic Institute and State University

Time: July 17, 2024, 10:00 AM

Venue: EMS 319

Abstract: Artificial intelligence (AI) is a vast area of computer science focused on creating machines capable of perceiving their environment and performing tasks typically requiring human intelligence. AI encompasses several interrelated fields, including computer vision (detecting images), natural language processing (understanding written language), speech recognition (interpreting spoken language), and machine learning/deep learning. As organizations implement machine learning, many traditional marketing methods will either become obsolete or undergo significant transformations. Algorithms will enhance the efficiency and effectiveness of tasks like market structure analysis and competitor identification. However, machine learning methods can be resource-intensive, with algorithms taking considerable time to converge, especially with large datasets. Future efforts to integrate new technologies, such as quantum computing, with machine learning methods will further reduce computational costs and unlock new research opportunities.

Guest Bio: Professor Wang Xin is currently a tenured full professor at Virginia Tech's Pamplin College of Business, a doctoral advisor, and the director of graduate and postgraduate programs. Professor Wang is the only Chinese member on the academic committee of the AMA North American Marketing Association (12-member panel), and currently serves as an associate editor for the Journal of Marketing, Production and Operation Management, and the Journal of the Academy of Marketing Science. He is also a member of the editorial boards for Journal of Marketing Research and Journal of Consumer Research, and serves as a reviewer for numerous economic and management journals, as well as for national research funding projects. His research areas include the commercial applications of artificial intelligence, big data mining, and corporate strategy research, marketing and fintech, market structure and brand relationships, social network analysis, internet marketing, consumer product choice and behavioral economics; his research findings have been published in top international academic journals such as Marketing Science, Journal of Consumer Research, Management Science, Journal of Marketing Research, Journal of Marketing, and International Journal of Research in Marketing. Based on the statistics of the North American Marketing Association over the past decade, Professor Wang is one of the top 50 most productive scholars in the world in terms of the number of articles published in top marketing journals. Before joining Virginia Tech, Professor Wang taught at the Marketing Department of the Ivey Business School at Western University in Canada, where he was a tenured full professor, a distinguished visiting professor at the Cable Group, and a dual-appointed professor in the departments of Statistics and Actuarial Science. Professor Wang has received the AMA Journal of Practical Marketing Best Paper Award twice in 2021 and 2023 (the only scholar to receive the award twice), the AMA Best Dissertation Advisor Award (Nomination Award, Donald Lehmann Award Finalist) in 2023, the MSI Outstanding Young Scholar Award in 2021, the Best Paper Award at the annual North American Marketing Winter Conference in 2013 and 2018, and numerous other teaching and research awards.