Matteo Riondato

Head shot of Matteo Riondato
				by Andrea Podestà

Contact info

I am a researcher in computer science, currently with the Labs group at Two Sigma, a highly innovative investment firm in New York City. I also have an appointment as Visiting Assistant Professor of Computer Science at Brown University.

My research interest is in algorithmic data science. 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).


  • FouLarD'18: I'm co-organizing FouLarD'18, a workshop on the foundations of learning from data, together with Mehryar Mohri, Alessandro Panconesi, and Eli Upfal. It will take place in Bertinoro, Italy, in September 2018.
  • ECML PKDD'18: Happy to serve on the PC of ECML PKDD'18, my "home" conference in many ways, and a great venue for algorithmic data science.
  • Grace Hopper'18: I'm proud to be serving on the program commitee for the Data Science track of the Grace Hopper Celebration, the premier event for women technologists.
  • Talk at Harvard: On 4/30 I'll be speaking at the Theory of Computation Semininar at Harvard. Thanks to Mike Mitzenmacher for inviting me.
  • ACM CIKM'18: I'm on the PC of ACM CIKM'18, which takes place in Turin in October.
  • ACM KDD'18: I'll be serving on the PC of ACM KDD'18, the major conference on data mining.
  • Teaching at Brown CS: I'm teaching CSCI 1951-G Optimization Methods in Finance again in Spring'18. So rewarding to be in class with brilliant students again!
  • SIAM SDM'18: I'll be the sponsorship co-chair for SIAM SDM'18. I'm excited to contribute to the organization of this great conference stressing the importance of theory in data mining.
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