Guilherme Rocha

Guilherme Rocha is an Assistant Professor in the Department of Statistics at the University of California, Berkeley. He completed his Ph.D. in Statistics at UC Berkeley in 2008 under the supervision of Bin Yu, with a dissertation titled 'Sparsity and model selection through convex penalties: Structured selection, covariance selection and some theory'.

His research focuses on statistical machine learning methodologies, particularly sparsity-inducing techniques, high-dimensional data analysis, model selection frameworks, and convex optimization approaches for structured data problems. These interests align with the department's research strengths in artificial intelligence and high-dimensional inference.

No awards, student advisements, publications, or external grants are detailed in the available information.