Yaniv Plan

Yaniv Plan is a faculty member in the Department of Mathematics at The University of British Columbia. His research interests are not specified in the available information. He can be contacted via email at yaniv@math.ubc.ca or through his personal website. His profile page indicates his affiliation with the university and provides contact details, but no further details about his academic background, awards, or specific research areas are provided.

Yaniv Plan is a researcher at the University of British Columbia, specializing in mathematical signal processing, compressive sensing, matrix completion, and learning theory. His work focuses on developing theoretical frameworks for reconstructing signals and matrices from incomplete or noisy data. Plan's research includes analyzing the performance of algorithms for low-rank matrix recovery, compressed sensing with non-Gaussian measurements, and robust statistical learning under sparse alternatives. His contributions span both probabilistic and deterministic analyses of high-dimensional estimation problems, emphasizing the interplay between geometry, convex optimization, and statistical learning. His publications address challenges in model selection, error bounds, and the design of efficient recovery algorithms for structured data.