Tuesday Nov. 29, 2022
Colloquium: Ying Ding (UT iSchool) - Team: Power, Leadership, and Diversity
12:30 to 2 p.m.
Hybrid: Zoom & UTA 5.522 (Large Conference Room)

Abstract: Team becomes the fundamental unit to create innovation. How to form an effective team is the question that everyone deeply cares, whether you are a leader of a multinational company or a student from a local community college. This talk unveils the insights of a comprehensive study of several millions of teams from different academic fields about their team formation and team performance. It highlights the understanding of teams from the perspectives of team power, shared leadership, and diversity. Flat team structure, heterogeneous shared leadership, and rich diversity are different pathways for team success.

Bio: Dr. Ying Ding is Bill & Lewis Suit Professor at School of Information, and adjunct Professor at Department of Population Health at Dell Medical School, University of Texas at Austin. She leads the AI in Health Lab at School of Information and Dell Medical School with the focus on medical imaging, medical notes summary, health risk prediction, and explainable AI. Before that, she was a professor and director of graduate studies for data science program at School of Informatics, Computing, and Engineering at Indiana University. She has led the effort to develop the online data science graduate program for Indiana University. She has been involved in various NIH, NSF and European-Union funded projects. She has published 300+ papers in journals, conferences, and workshops, and served as the program committee member for 200+ international conferences. She is the general co-chair of The Web Conference 2023 in Austin. She is the co-editor of book series called Semantic Web Synthesis by Morgan & Claypool publisher, the co-editor-in-chief for Data Intelligence published by MIT Press, and serves as the editorial board member for several top journals in Information Science and Semantic Web. She is the co-founder of Data2Discovery company advancing cutting edge AI technologies in drug discovery and healthcare. Her current research interests include medical imaging, knowledge graph, graph deep learning, AI in health, data-driven science of science, and team collaboration.

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