Leonardo Pellegrina

I am a Postdoctoral Researcher at the Department of Information Engineering of the University of Padova. In my research I work on providing novel efficient and statistically sound algorithms for knowledge and pattern discovery from data, often motivated by biological applications.
I obtained my Ph.D. in Information Engineering from the Department of Information Engineering of the University of Padova, under the supervision of Prof. Fabio Vandin (Vandin Lab website). I also had the amazing opportunity of visiting the Department of Computer Science of Brown University, as a Visiting Research Fellow under the supervision of Prof. Eli Upfal.

Links and contacts
Curriculum Vitae, List of publications, Google scholar, Twitter, GitHub page, mail: leonardo.pellegrina@unipd.it.

- June 2021: A preprint of our work "SILVAN: Estimating Betweenness Centralities with Progressive Sampling and Non-uniform Rademacher Bounds" is available online.
- May 2021: We presented the second edition of our tutorial "Hypothesis Testing and Statistically-sound Pattern Mining" at SDM 2021.
- Mar. 2021: I successfully defended my Ph.D. thesis "Rigorous and Efficient Algorithms for Significant and Approximate Pattern Mining"!
- Feb. 2021: Our paper "SPRISS: Approximating Frequent k-mers by Sampling Reads, and Applications", with Diego Santoro and Fabio Vandin, has been accepted to RECOMB 2021!
- Dec. 2020: I won a two-year research grant ("Junior type B" grant) from the Department of Information Engineering! I am really excited for this opportunity and for the work to come.
- Oct. 2020: A preprint of my work "Sharper convergence bounds of Monte Carlo Rademacher Averages through Self-Bounding functions" is available online.
- May 2020: Our paper "MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining", with Cyrus Cousins, Fabio Vandin, and Matteo Riondato, has been accepted to KDD 2020!
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