Our research group is part of the School of Computer and Communication Sciences at EPFL in Lausanne, Switzerland. The group is lead by Matthias Grossglauser and Patrick Thiran. Our research focuses broadly on the statistical modeling of large dynamical systems involving both human and technical agents. Examples include social and information networks, epidemic processes, human mobility and transportation, and recommender systems. Our work lies at the intersection of machine learning, probabilistic modeling, large-scale data analytics, and performance analysis. Here are the research areas we work on:
On the robustness of the metric dimension of grid graphs to adding a single edge S. Mashkaria, G. Odor and P. Thiran Discrete Applied Mathematics, 2022-07-31.
The power of adaptivity in source identification with time queries on the path V. Lecomte, G. Odor and P. Thiran Theoretical Computer Science, 2022-04-08.
Augmenting and Tuning Knowledge Graph Embeddings R. Bamler, F. Salehi and S. Mandt 35th Uncertainty in Artificial Intelligence (UAI) Conference, Tel Aviv, ISRAEL, Jul 22-25, 2019.
Sequential metric dimension for random graphs G. Odor and P. Thiran Journal of Applied Probability, 2021.
Switchover phenomenon induced by epidemic seeding on geometric networks G. Odor, D. Czifra, J. Komjáthy, L. Lovász and M. Karsai Proceedings of the National Academy of Sciences, 2021.