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Biography
Zihang Lin is a PhD candidate in the Department of Industrial Engineering & Management Sciences (IEMS) of the McCormick School of Engineering at Northwestern University. He is affiliated with Kellogg Center for Science of Science & Innovation and Northwestern Institute on Complex Systems, under the supervision of Prof. Dashun Wang. He has also been fortunate to work closely with Prof. Benjamin F. Jones. He earned his master’s degree in Northwestern IEMS in 2024. Previously, he received his bachelor’s degree in computer science from Fudan University in June 2023, where he was advised by Prof. Yang Chen. During 2021 and 2022, he was a Visiting Predoctoral Fellow at the Kellogg School of Management, Northwestern University.
His research interests encompass computational social science, science of science, and innovation. Recently, his endeavors have been concentrated on extensive data analyses with advanced machine learning techniques, in a quest to achieve a deeper understanding of science and innovation. Specifically, he is interested in how prior scientific knowledge supports tomorrow’s technological breakthroughs, aiming to accelerate the translational impact of research and foster innovation ecosystems.
Download my Curriculum Vitae.
- Computational Social Science
- Science of Science
- Innovation
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PhD candidate in Industrial Engineering & Management Sciences, 2023-now
McCormick School of Engineering, Northwestern University
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M.S. in Industrial Engineering & Management Sciences, 2024
McCormick School of Engineering, Northwestern University
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B.S. in Computer Science, 2023
School of Computer Science, Fudan University
Experience
Research
Featured Publications
SciSciNet, a large-scale open data lake for the science of science research, covers over 134M scientific publications and millions of external linkages to funding and public uses, and serves as an initial but useful resource for the field.
A comprehensive review on the foundation, detection and practical application of structural hole theory, facilitating researchers and developers to better apply structural hole theory and derive value-added tools.