I am currently doing my PhD at EPFL in Computer Science working with Prof. Michael Kapralov. My main research interests are sublinear algorithms for graph analysis. In particular I have worked on sparsification, matchings, and clustering in various regimes of sublinear computation.

Publications

1. Michael Kapralov, Amulya Musipatla, Jakab Tardos, David P. Woodruff, Samson Zhou.
   Noisy Boolean Hidden Matching with Applications.
   ITCS 2022.
   [arxiv link]

2. Michael Kapralov, Silvio Lattanzi, Navid Nouri, Jakab Tardos.
   Efficient Local Parallel Random Walks.
   NeuRIPS 2022.

3. Yuchen Wu, Jakab Tardos, MohammedHossein Bateni, Andre Linhares, Filipe Miguel Goncalves de Almeida, Andrea Montanari, Ashkan Norouzi-Fard.
   Streaming Belief Propagation for Community Detection.
   NeuRIPS 2022.
   [arxiv link]

4. Michael Kapralov, Robert Krauthgamer, Jakab Tardos, Yuichi Yoshida.
   Spectral Hypergraphs of Nearly Linear Size.
   FOCS 2021.
   [arxiv link]

5. Michael Kapralov, Robert Krauthgamer, Jakab Tardos, Yuichi Yoshida.
   Towards Tight Bounds for Spectral Sparsification of Hypergraphs.
   STOC 2021.
   [arxiv link]

6. Michael Kapralov, Gilbert Maystre, Jakab Tardos
   Communication Efficient Coresets for Maximum Matching.
   SOSA 2021.
   [arxiv link]

7. Marwa El Halabi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakab Tardos, Jakub Tarnawski.
   Fairness in Streaming Submodular Maximization: Algorithms and Hardness.
   NeuRIPS 2021.
   [arxiv link]

8. Michael Kapralov, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakab Tardos.
   Space Efficient Approximation to Maximum Matching Size from Uniform Edge Samples.
   SODA 2020.
   [arxiv link]

9. Michael Kapralov, Navid Nouri, Aaron Sidford, Jakab Tardos.
   Dynamic Streaming Spectral Sparsification in Nearly Linear Time and Space.
   SODA 2020.
   [arxiv link]