Sayan Mukherjee

Faculty, Scholars, & Staff
Statistical Science

Research interests

  • Statistical and computational methodology in genetics, cancer biology, metagenomics, and morphometrics;
  • Bayesian methodology for high-dimensional and complex data;
  • Machine learning algorithms for the analysis of massive biological data;
  • Integration of statistical inference with differential geometry and algebraic topology;
  • Stochastic topology;
  • Discrete Hodge theory;
  • Inference in dynamical systems.