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 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: TipTap, our work on maintaining frequent subgraphs in fully-dynamic edge graph streams has been accepted to ACM TKDD. Nice work using reservoir sampling and random pairing, with Gianmarco, Cigdem, and Anis.
- Fidelity (10/28): giving a talk on MCRapper at Fidelity, thank you Serdar for inviting me.
- WSDM'21: "RepBubLik: Reducing the Polarized Bubble Radius with Link Insertions" was accepted to WSDM'21, a venue dear to me. Joint work with the Brown crew: Shahrzad Haddadan, Cristina Menghini, and Eli Upfal.
- UMass talk (10/6): I'll be giving a talk on MCRapper at the Theory seminar. Thanks Cameron for inviting me!
- NeurIPS'20: our paper (w/ soon-to-be-PhD-extraordinaire Cyrus Cousins) "Sharp uniform convergence bounds through empirical centralization" was accepted. This work is theoretical and fun!
- NSF Grant: My project on Scalable and Iterative Statistical Testing of Multiple Hypotheses on Massive Datasets has been funded! Thanks NSF! I really look forward to the work ahead.
- SDM'21: I will be the Tutorial Chair and a member of the Senior PC for SIAM SDM'21. Always glad to be of service to the knowledge discovery, data mining, and statistics communities.
- KDD'20: MCRapper, our work on computing the Monte Carlo Empirical Rademacher Average on poset families for approximate pattern mining has been accepted as a full paper in the research track. Join work with the statistics-datamining gang: Leonardo Pellegrina, Cyrus Cousins, and Fabio Vandin.
- News archive