RESEARCH INTERESTS

My interests are in harmonic analysis, wavelets, multiscale analysis in general, and in particular with applications to the analysis of graphs and data sets viewed as discrete or sampled continuous geometric structures embedded in high-dimensional spaces. I am interested in machine learning problems, mostly from the point of view of approximation and fitting of functions under random noise and random sampling.

  1. Diffusion Wavelets: a recent construction of new families of wavelets and Multi-resolution Analyses on graphs, manifolds and point clouds. Pictures, papers and presentations available.
  2. Diffusion Geometries: here are some links to the use of diffusion geometries in data analysis.
  3. Multiscale Analysis of Markov Decision Processes
  4. Harmonic Analysis and Wavelets: here I talk a bit about Harmonic Analysis and provide links to related web pages.
  5. HyperSpectral Imaging and Pathology : hyper-spectral imaging applied to pathology

Current students and postdocs

Prakash Balachandran, Yoon-Mo Jung, Anna V Little.

New!

Our Probability Wiki at Duke. As of Spring 09, we are meeting every Tuesday at 1pm in Room 259 in the Physics building, to discuss topics of interest to the audience. It is informal, highly interdisciplinary, and fun. Papers/talks are collected on the wiki. Feel free to join us (or the mailing list).

Symposium on Manifold Learning to be held on Nov. 5-7 in Arlington, VA.

The Compressive Sensing Workshop at Duke (slides and video lectures available).

Links of Interest

Programming, Code, etc...

Data Sets

Some Google searches