In theory there is no difference between theory and practice. In practice there is. -Yogi Berra

Our group combines expertise in structural graph theory, efficient algorithms, and generative network models with tools from geometry and statistics to address fundamental questions in data-driven science.

Most of our current research focuses on improving the understanding of intermediate-scale network structure, and using it to develop new efficient (parameterized) algorithms for rigorous, robust comparison, anomaly detection, sampling, and feature approximation in real-world graph data.

Recent News

  • August 1, 2016

    Welcome to our Fall 2016 undergraduate researchers: Eric Horton and Jean-Claude Shore! (now on the People page.)

  • July 25, 2016

    Joint paper with Ph.D. student Andrew van der Poel "A Fast Parameterized Algorithm for Co-Path Set" accepted at IPEC 2016!

  • July 17, 2016

    #SIAMNS16 had a record number of submissions -- and attendees! Members of Theory in Practice had five accepted abstracts (2 posters, 2 talks, 1 IGNITE).