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:
Recovering Static and Time-Varying Communities Using Persistent Edges K. Avrachenkov, M. Dreveton and L. Leskela Ieee Transactions On Network Science And Engineering, 2024.
It’s All Relative: Learning Interpretable Models for Scoring Subjective Bias in Documents from Pairwise Comparisons A. Suresh, C. H. Wu and M. Grossglauser 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2024), Malta, March 17th -22nd, 2024.
Leveraging Unlabeled Data to Track Memorization M. Forouzesh, H. Sedghi and P. Thiran 11th International Conference on Learning Representations (ICLR 2023), Kigali, Rwanda, May 1-5, 2023.
Mining Effective Strategies for Climate Change Communication A. Suresh, L. Milikic, F. Murray, Y. Zhu and M. Grossglauser ICLR 2023 Workshop on Tackling Climate Change with Machine Learning, Kigali, Rwanda, May 4, 2023.
Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function S. Masiha, S. Salehkaleybar, N. He, N. Kiyavash and P. Thiran 2022.
We are hiring postdocs and PhD students in all our research areas.