معرفی
Youngsoo Kim is an Associate Professor and the James E. & Elizabeth F. Sowell Professor at the Rawls College of Business, Texas Tech University. He directs the Master of Science in Data Science Program and holds a PhD in Information Systems from Carnegie Mellon University, alongside BS and MS degrees from KAIST. His research focuses on network analytics, online market dynamics, and learning processes, with publications in top-tier journals like Management Science and Information Systems Research.
Education includes:
- PhD in Information Systems, Carnegie Mellon University
- MS in [unspecified field], Korea Advanced Institute of Science and Technology (KAIST)
- BS in [unspecified field], KAIST
Research Interests: Kim explores how online platforms and communication networks influence consumer behavior, organizational resilience, and knowledge transfer. His work bridges information systems theory with practical applications in e-commerce, crisis management, and open-source development. Notable themes include paywall strategies for news publishers, chatbot interaction patterns, and AI-driven software productivity.
Advising & Grants: While formal student listings or grant details are not provided, his leadership role in the Data Science Program indicates active involvement in academic mentorship and program development. His research has been supported through institutional and collaborative funding avenues.
Labs/Teams: Engaged in interdisciplinary teams within the Rawls College, focusing on data science and business analytics initiatives. Collaborations likely span technology, marketing, and organizational behavior domains.
