Leonardo Pellegrina
I am an Assistant Professor (RTDa) at the
Department of Information Engineering (DEI)
of the University of Padova, and part of the AIDA Lab.
In my research I develop practical, and theoretically sound, algorithms for Data Mining and Computational Biology.
Previously, I was a PostDoc and Ph.D. student at the University of Padova,
under the supervision
of Prof. Fabio Vandin.
I also was a Visiting Research Fellow at the
Department of Computer Science of Brown University, under the supervision of Prof. Eli Upfal.
Links and contacts
Curriculum Vitae,
Publications,
Google Scholar,
Twitter,
GitHub,
mail: leonardo.pellegrina *at* unipd.it
News
- May 2024: Our paper "Scalable Rule Lists Learning with Sampling" has been accepted to KDD 2024!
- May 2024: Our paper "Efficient Discovery of Significant Patterns with Few-Shot Resampling" has been accepted to VLDB 2024!
- October 2023: Our paper "SILVAN: Estimating Betweenness Centralities with Progressive Sampling and Non-uniform Rademacher Bounds" has been accepted to ACM TKDD!
- August 2023: I will join ScalPerf 2023 in Bertinoro to talk about our recent "Statistical learning techniques to efficiently identify central nodes from large graphs".
- July 2023: A short version of our SILVAN paper has been accepted to the MLG workshop at ECML PKDD 2023! See you in Turin!
- May 2023: My paper "Efficient Centrality Maximization with Rademacher Averages" has been accepted to KDD 2023!
All News