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Hello!
Welcome to my webpage. I am a post-doctoral researcher at EPFL, affiliated to the group of Prof. Emmanuel Abbé in the Mathematics Institute, working on mathematics and reasoning in AI. Until now, I did most of my research in Theoretical Computer Science (specifically Combinatorial Optimization), but since 2025, I am also very interested in the topic of AI for mathematics. You can find more info about me here.
Contact
Projects and advising
Below you can find the list of my publications. I also advised several student projects/MSc theses either on algorithms and theory or on more applied projects (see poster for a more applied example).
Publications
All my publications can also be found on my scholar profile.
E. Bamas, SG Nagarajan, O. Svensson. An Analysis of $D^alpha$ seeding for k-means.
[arXiv, conference version], in ICML 2024.
E. Bamas, A. Lindermayr, N. Megow, L. Rohwedder, J. Schloeter. Santa Claus meets Makespan and Matroids: Algorithms and Reductions.
[arXiv], in SODA 2024 (invited to TALG special issue).
E. Bamas, M. Drygala, O. Svensson. A Simple LP-Based Approximation Algorithm for the Matching Augmentation Problem.
[arXiv], in IPCO 2022.
E. Bamas, M. Drygala, A. Maggiori. An Improved Analysis of Greedy for Online Steiner Forest.
[arXiv], in SODA 2022 (student authors only).
E. Bamas, P. Garg, L. Rohwedder. The Submodular Santa Claus Problem in the Restricted Assignment Case.
[arXiv], in ICALP 2021.
E. Bamas, A. Maggiori, O. Svensson. The Primal-Dual method for Learning Augmented Algorithms.
[arXiv], in NeurIPS 2020 (oral presentation, top 1% of submissions).
E. Bamas, A. Maggiori, L. Rohwedder, O. Svensson. Learning Augmented Energy Minimization via Speed Scaling.
[arXiv], in NeurIPS 2020 (spotlight presentation, top 3% of submissions).
E. Bamas, L. Esperet. Local Approximation of the Maximum Cut in Regular Graphs.
[arXiv], in WG 2019, journal version in Theoretical Computer Science.
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