- Analysis of random measurements.
Short Course
"Sparse Representations and High Dimensional Geometry",
IPAM, UCLA, Los Angeles, CA, 2007
- Lecture 1: The Sparse reconstruction problem and random matrices
- Lecture 2: Upper and lower bounds for subgaussian matrices
- Lecture 3: Random Fourier matrices
- Commentary and Bibliography

- Uncertainty principles, frames, and quantization. Trends in Harmonic Analysis, Strobl, Austria, 2007.
- Anti-concentration inequalities. Phenomena in High Dimensions, Samos, Greece, 2007.
- Sparse representations and invertibility of random matrices, AMS 2007 Von Neumann Symposium, Snowbird, Utah, 2007
- Compressed Sensing. Applied Mathematics Seminar, UC Davis, 2007
- Small ball probability, additive structure and random matrices, DIMACS, Rutgers University, 2008
- On the role of sparsity in compressed sensing and random matrix theory, CAMSAP 09, Aruba, 2009
- Random matrix theory from the functional analytic perspective, SEAM XXVI, Georgia Tech, Atlanta, 2010
- Estimation of covariance matrices, Probability and Geometry in High Dimensions, Paris, France, 2010. A slightly modified version (with a discussion of Levy flights) is in my talk at UM Statistics.
- Non-asymptotic theory of random matrices and sparsity, Bonn Mathematical Colloquium and Workshop on Sparsity and Computation, Bonn, Germany, 2010
- Non-asymptotic theory of random matrices: extreme singular values, International Congress of Mathematicians, Hyderabad, India, 2010
- Covariance estimation and invertibility of random matrices, joint PACM Colloquium and Analysis Seminar, Princeton, 2011. A slightly edited version is a talk at MSU.
- Random matrices: invertibility, structure, and applications, Canadian Mathematical Society Summer Meeting, Edmonton, Alberta, 2011.
- 9-hour course on non-asymptotic analysis of random matrices, Summer School on Random matrices - stochastic geometry - compressed sensing, Institut Henri Poincare, France, 2011.
- Invertibility of symmetric random matrices, Random Matrices, Bonn, Germany, 2012.
- New ways of dimension reduction? Cutting data sets into small pieces, Statistical Learning and Data Mining, Ann Arbor, 2012.
- Random hyperplane tessellations and dimension reduction, Phenomena in high dimensions in geometric analysis, random matrices and computational geometry, Roscoff, France, 2012.
- Probabilistic reasoning in compresses sensing, Journees MAS, Clermont-Ferrand, France, 2012.
- Smoothed analysis of random matrices, Asymptotic Geometric Analysis II, Saint-Petersburg, Russia, 2013.
- Sampling and high-dimensional convex geometry, SampTA 2013, Bremen, Germany.
- Random matrices: recent progress in theory and applications,
University of Michigan, 2013.

At this moment, only scanned notes of these lectures are available. - Delocalization of eigenvectors or random matrices, AMS Special Session on Random Matrices, Baltimore, 2014.