I am an assistant professor of computer science at Amherst College, where I lead the Data* Mammoths, a research&learning group of brilliant undergraduate students. I also have an appointment as visiting faculty in Computer Science at Brown University. Previously, I spent some fantastic years as a research scientist in the Labs group at Two Sigma.
My research focuses on algorithms for knowledge discovery, data mining, and machine learning. I develop theory and methods to extract the most information from large datasets, as fast as possible and in a statistically sound way. The problems I study include pattern extraction, graph mining, and time series analysis. My algorithms often use concepts from statistical learning theory and sampling. My research is supported, in part, by NSF Award #2006765.
My Erdős number is 3 (Erdős → Suen → Upfal → Matteo), and I am a mathematical descendant of Eli Upfal, Eli Shamir (2nd generation), Jacques Hadamard (5th), Siméon Denis Poisson (9th), and Pierre-Simon Laplace (10th).
News
- TKDD: the extended version of MCRapper was accepted to ACM TKDD. An elegant algorithm to compute Rademacher averages for families of function with a natural poset structure, which are omnipresent in pattern mining. Nice collab with Leonardo, Cyrus, and Fabio.
- AAAI'22: the Data* Mammoths' work on parallel algorithms for cube sampling was accepted for publication as a student abstract/poster to AAAI'22. Fun work by brilliant undergraduate researchers: it started with Shukry's honors thesis, and Alex and Stefan brought it to completion.
- SDM'22: I'm excited and honored to be PC-chair of SIAM SDM'22, together with the great Vagelis Papalexakis, and a wonderful OC. Looking forward to receiving interesting submissions on data mining, knowledge discovery, and its statistical aspects.
- News archive