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FORTHCOMING EVENT

SIG-MET Distinguished Speaker Series: Lecture by Dr. Yong-Yeol (YY) Ahn

Speaker: Dr. Yong-Yeol (YY) Ahn

Dr. Yong-Yeol (YY) Ahn is a network and data scientist whose work combines network science, machine learning, and the study of complex social, biological, and information systems. He is a Quantitative Foundation Distinguished Professor at the University of Virginia’s School of Data Science. Before joining UVA, he was a Professor at Indiana University’s CNetS, Luddy School of Informatics, Computing, and Engineering and a Visiting Professor at MIT. Earlier, he worked as a postdoctoral research associate at the Center for Complex Network Research at Northeastern University and as a visiting researcher at the Center for Cancer Systems Biology at Dana-Farber Cancer Institute after completing his PhD in Statistical Physics from KAIST. His research focuses on the architectures of complex systems—how networks shape behavior, cognition, and scientific progress—and on developing methods in network analysis, machine learning, and natural language processing to investigate these mechanisms at scale. He is the co-author of Working with Network Data. His work has been recognized with several honors, including the Microsoft Research Faculty Fellowship.

Title: The Geometry of Science

What would scientometrics look like if scientific ideas lived in a concrete physical space? Deep representation learning now allows us to imagine such a shared knowledge embedding space where scholarly works, ideas, and other entities can coexist. Yet these powerful models are often black boxes, hard to translate into interpretable metrics. In this talk, I show that a fundamental understanding of embedding methods can make this space interpretable, allowing its geometry to be measured directly. The flow of scientists between institutions follows a gravity law governed by distance in the space, and scientific disruption can be captured through the geometric displacement of a field's trajectory — without relying on sparse local citation links. This embedding-based framework may offer a unified language for describing how science attracts, disrupts, and moves, complementing traditional citation-based indicators.

Lecture Guide:

Registration - https://www2.asist.org/ap/Events/Register/xRFXn32sMCYC7

Location - Online event, the lecture link will be sent to registered attendees via email.

Time - 9:00-10:00 AM (EDT) USA time on Tuesday, March 17th, 2026.

Organizers:

ASIS&T SIG-MET

Faculty of Education, The University of Hong Kong

School of Information Management, Sun Yat-sun University

 

PAST EVENTS

SIG-MET Distinguished Speaker Series: Opening Lecture by Dr. Cassidy Sugimoto

Speaker: Dr. Cassidy Sugimoto

Dr. Cassidy Sugimoto is Tom and Marie Patton Professor and School Chair in the School of Public Policy at Georgia Institute of Technology. Her research examines the formal and informal ways in which knowledge is produced, disseminated, consumed, and supported, with an emphasis on issues of diversity, equity, and inclusion.

Title: How to Be a Scientific Superpower

This talk explores the systemic factors and policy frameworks that enable nations and institutions to achieve scientific excellence and global influence in research. Drawing on her metascience research, Sugimoto explores how indicators around investments and production have been the primary drivers of what constitutes a "superpower". Weaving together historical evidence, she argues for indicators that consider diffusion and epistemic influence and demonstrates the current polycentric organization of global science. The conclusion will focus on how scientists, policymakers, and administrators can be more intentional in setting the global scientific agenda.

Conference Guide:

Registration - https://www2.asist.org/events/Details/sig-met-invited-talk-1-1565651?sourceTypeId=Hub

Location - Online event, the lecture link will be sent to registered attendees via email.

Time - 9:00-10:00 am USA time on Friday, December 5th, 2025.

Sponsors: