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 (2^{nd} generation), Jacques
Hadamard (5^{th}), Siméon
Denis Poisson (9^{th}), and Pierre-Simon
Laplace (10^{th}).

## 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