I am a Ph.D. student in Information Engineering from the Department of Information Engineering of the University of Padova. My advisor is Prof. Fabio Vandin (Vandin Lab website).
My research interests extend to Data Mining, Machine Learning, Computational Biology and Statistics. In particular, I work on providing novel efficient and statistically sound algorithms for pattern discovery from (small and large) data. One of my main goals is to apply such methods to the analysis of biological data.
You can read my CV (updated at 5/2019), contact me at pellegri@dei.unipd.it, and visit my GitHub page.

News
- Apr. 2019: Our paper "SPuManTE: Significant Pattern Mining with Unconditional Testing" and our tutorial on Multiple Hypothesis Testing and Statistically-sound Pattern Mining (with Matteo Riondato and Fabio Vandin) have been accepted to KDD 2019!
- Feb. 2019: I received the RECOMB 2019 Travel Fellowship, funded by the International Society for Computational Biology (ISCB)! Can't wait to attend this year RECOMB in Washington and to present our work.
- Dec. 2018: our paper "Fast Approximation of Frequent k-mers and Applications to Metagenomics", in collaboration with Cinzia Pizzi and Fabio Vandin, has been accepted to RECOMB 2019!
- Oct. 2018: From January to July 2019 I will be a Visiting Research Fellow of the Department of Computer Science of Brown University!
- Sept. 2018: I am thrilled to join FouLarD'18, the Workshop on Foundations of Learning from Data held in Bertinoro, a great opportunity to meet and learn from amazing researchers and experts in the field.
- May 2018: our paper "Efficient Mining of the Most Significant Patterns with Permutation Testing", in collaboration with Fabio Vandin, has been accepted to KDD 2018!