I am an assistant professor of computer science at Amherst College. 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 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
- NetSciI@NEU (11/8): I'll be giving a talk at the Network Science Institute at Northeastern University. Thank you Tina for inviting me: the place and people there are wonderful and do super cool work.
- MassMutual Research Bytes(11/5): I'll be giving a talk on making better use of data through hypothesis testing and statistical learning theory. Thank you Nick for inviting me.
- BU (10/25): I'll be giving a talk at Boston University. Thank you Evimaria for inviting me.
- MHC (10/16): I'll be giving a talk at Mount Holyoke College. Thanks to Valerie for inviting me.
- CaStleD'19: I'm giving a talk on CaDET at CaStleD'19 in Bertinoro. Thank you Fabio for inviting me.
- ECML PKDD: CaDET, our algorithm for interpretable conditional density estimation using decision trees has been accepted to the special issue of Machine Learning for ECML PKDD'19. Joint work with thinker-extraordinaire PhD student Cyrus Cousins.
- News archive