Minsuk Daniel Kim 

About Me

I am an Informatics Ph. D. candidate at Indiana University, specializing in Complex Networks and Systems. My research explores the interplay between transportation infrastructure, human mobility, and the accessibility of urban amenities. I employ tools from network science, statistical physics, and machine learning to uncover the underlying dynamics that shape mobility patterns and urban accessibility. My work extends to broader topics such as phase transitions and dynamics on networks, unsupervised representation learning, and geospatial data analysis, with the goal of advancing our understanding of various complex systems.

Currently, I am actively collaborating with Prof. Filippo Radicchi on network optimization problems, especially focusing on transportation infrastructure networks. I am also working on the "invisible border" project which aims at capturing the latent structure of human mobility and urban accessibility via neural embedding with Prof. Yong-Yeol Ahn and Prof. Esteban Moro. Before joining IU, I worked on phase transition on complex networks with Prof. Soon-Hyung Yook at Kyung Hee University. 

Education

• Ph. D. in Informatics, Indiana University, Bloomington, IN, United States (Aug 2022 - )
  Track: Complex Networks & Systems

• M. Sc. in Physics, Kyung Hee University, Seoul, Korea (Mar 2019 - Feb 2021)
  Concentration: Statistical Physics 

• B. Sc. in Physics, Kyung Hee University, Seoul, Korea (Mar 2013 - Feb 2019)

Publications

[5] Effect of isolation strategies on epidemic spreading in multiplex networks with an annealed interactions layer
Minsuk Kim and S.-H. Yook
Journal of the Korean Physical Society 86, 73–84 (2025)

[4] Shortest-Path Percolation on Random Networks
Minsuk Kim and F. Radicchi
Physical Review Letters 133, 047402 (2024) 

[3] Reconstruction of multiplex networks via graph embeddings
D. Kaiser, S. Patwardhan, Minsuk Kim, and F. Radicchi
Physical Review E 109, 024313 (2024)[PDF]

[2] A multi-platform collection of social media posts about the 2022 US midterm elections
R. Aiyappa, M. R. DeVerna, M. Pote, B. Tran Truong, W. Zhao, D. Axelrod, A. Pessianzadeh, Z. Kachwala, M. Kim, O. C. Seckin, Minsuk Kim, S. Gandhi, A. Manikonda, F. Pierri, F. Menczer, and K.-C. Yang
Proceedings of the International AAAI Conference on Web and Social Media (ICWSM) 17 (Limassol, Cyprus, 2023), 981–989.

[1] Majority-vote model with degree-weighted influence on complex networks
Minsuk Kim and S.-H. Yook
Physical Review E 103, 022302 (2021) [PDF]