Cornell University · Department of Information Science
Yangfanyu Yang 楊 陽 笵 宇
Ph.D. student studying how knowledge ages, accumulates, and spreads — through the lenses of network science, computational social science, and the science of science.
About
I am a first-year Ph.D. student in Information Science at Cornell, advised by Yian Yin, with a special committee that includes Jon Kleinberg and Rene Kizilcec.
My research treats science as a complex system: I build network models and large-scale empirical analyses to understand how careers, citations, and ideas evolve over time — and what drives the inequalities that emerge along the way.
Before Cornell, I read Mathematics at St John's College, Cambridge and completed an M.S. in Statistics at the National University of Singapore.
Education
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2024–
Cornell University
Ph.D. student, Information Science.
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2025
St John's College, University of Cambridge
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2024
National University of Singapore
M.S., Statistics.
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2021
St John's College, University of Cambridge
B.A., Mathematics.
Publications & Working Papers
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working paper
Quantifying Ageing Effects in Innovative Careers
Presented at the International Conference on the Science of Science and Innovation (ICSSI 2025); the International Conference on Complex Networks and their Applications (Complex Networks 2025); and the International School & Conference on Network Science (NetSci 2026).
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under review
Benchmark Datasets for Lead–Lag Forecasting on Social Platforms
Submitted to SIGKDD 2026.
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journal
Information Dissemination with Service-Oriented Incentive Mechanism in Industrial Internet of Things
IEEE Internet of Things Journal, vol. 9, no. 18, pp. 16897–16907, 2022. doi:10.1109/jiot.2022.3147840
Research Experience
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2021
Chongqing University of Posts and Telecommunications
Information Dissemination with Service-Oriented Incentive Mechanism. Co-authored an IEEE IoT Journal paper modelling how incentives shape information spread in industrial IoT networks, including simulation and stochastic analysis of the device-level dynamics.
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2017
Bulgarian Academy of Sciences · American University in Bulgaria
Predicting the Existence of Dark Matter in the Virgo Cluster. Estimated virial masses and luminosities of cluster galaxies to test for missing-mass signatures, with guidance from Nikola Karavasilev.