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  • Contact Info

Bhat, Sujeet Instructor


Research Areas research areas


research overview

  • Some of my research interests include studying problems that arise from or involve materials. I have studied composite materials using multiple scales analysis to study problems related to conductivity over heterogeneous electrode surfaces. This work required a deep analysis of the partial differential equations (PDEs) modeling the phenomena using asymptotic scales as well as a rigorous numerical solution of the PDEs. Another field of my research includes modeling and analyzing data using a data mining/machine learning approach based on spectral graph theory methods, probability and statistics. Large data sets are modeled on manifolds using a graph Laplacian approach. My recent work in this area involves using a graph theory based learning algorithm to perform a pattern analysis of synaptic activity induced by seizure-like events as well as using spectral graph theory based dimension reduction algorithms to analyze simulated radar and ladar data.


  • partial differential equations, asymptotics, numerical analysis, graph theory, probability and statistics


courses taught

  • APPM 4840 Reading and Research in Applied Mathematics (Spring 2019)
  • APPM 3170 Discrete Applied Mathematics (Fall 2018)
  • APPM 3570 Applied Probability (Fall 2018)
  • APPM 3310 Matrix Methods and Applications (Summer 2018)
  • APPM 1350 Calculus 1 for Engineers (Spring 2018)
  • APPM 3170 Discrete Applied Mathematics (Spring 2018)
  • APPM 4840 Reading and Research in Applied Mathematics (Spring 2018)


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