..

loosely woven

Research

Keywords: Network Science, Representation Learning, Science of Science, Human-Computer Interaction

Talks

Turning Spatial Intuition into Modeling with Neural Embeddings

CompleNet 2026, Zaragoza, Spain (May 4-8, 2026)

Selected works

Uncovering simultaneous breakthroughs with a robust measure of disruptiveness

Kim, M., Kojaku, S., & Ahn, Y. Y. (2025). Uncovering simultaneous breakthroughs with a robust measure of disruptiveness. Science Advances.

Aiyappa, R., Wang, X., Kim, M., Seckin, O. C., Yoon, J., Ahn, Y. Y., & Kojaku, S. (2025). Implicit degree bias in the link prediction task. ICML 2025.

Network community detection via neural embeddings

Kojaku, S., Radicchi, F., Ahn, Y. Y., & Fortunato, S. (2024). Network community detection via neural embeddings. Nature Communications, 15(1), 9446.

Unsupervised embedding of trajectories captures the latent structure of scientific migration

Murray, D., Yoon, J., Kojaku, S., Costas, R., Jung, W. S., Milojević, S., & Ahn, Y. Y. (2023). Unsupervised embedding of trajectories captures the latent structure of scientific migration. Proceedings of the National Academy of Sciences, 120(52), e2305414120.