I am Gordon McKay Professor of Electrical Engineering and of Applied Mathematics at the Harvard John A. Paulson School of Engineering and Applied Sciences.
I study the mathematical foundations of statistical signal processing and machine learning in high dimensions. In the past, I have also worked on imaging, multidimensional sampling theory, multiscale geometrical representations, and image processing.
News
- (11/28/21) IEEE Signal Processing Society Distinguished Lectureship
- (01/19/21) Householder Dice: a new matrix-free algorithm for simulating dynamics on random matrices
- (01/06/21) New paper: Phase transitions in transfer learning with high-dimensional perceptrons
- (09/26/20) NeurIPS paper: High-dimensional perceptrons: Approaching Bayes error with convex optimization
- (09/17/20) New paper: Universality Laws for High-Dimensional Learning with Random Features
- (08/28/20) New paper: A Precise Performance Analysis of Learning with Random Features
- (06/16/20) New paper: The limiting Poisson law of massive MIMO detection
- (06/02/20) ICML paper: The role of regularization in classification of high-dimensional Gaussian mixture
- (09/04/19) NeurIPS paper: A solvable high-dimensional model of GAN
- (05/01/19) ICML paper: Approximate survey propagation for high-dimensional estimation
- (03/28/19) New paper: Asymptotics and optimal designs of SLOPE
- (11/08/18) New paper: Optimal spectral method for high-dimensional signal estimation
- (10/19/18) Elected to the Big Data Special Interest Group (SIG) of the IEEE Signal Processing Society
- (09/26/18) New paper: Nonconvex optimization meets low-rank matrix factorization
- (05/27/18) Phase retrieval via polytope optimization: Geometry, phase transitions, and new algorithms
- (05/08/18) Subspace estimation from incomplete observations: a high dimensional analysis
- (05/02/18) Paper to appear at the Proceedings of the IEEE (Streaming PCA and subspace tracking: the missing data case)
- (04/16/18) ICASSP tutorial on nonconvex methods for high-dimensional statistical estimation (slides available online)
- (12/11/17) Best Student Paper Award (First Prize) at IEEE CAMSAP
- (12/06/17) Understanding the Dynamics of Online Learning Algorithms via Scaling and Mean-Field Limits