Alessandro Rinaldo

Professor | Department of Statistics and Data Sciences | IFML
The University of Texas at Austin

Email: alessandro.rinaldo@austin.utexas.edu
Website: https://arinaldo.github.io
Tel: +1 512 475 8722
Office: WEL 5.216G, Welch Hall, 105 E 24th Street Austin, TX 78712, USA

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I obtained my Ph.D. in Statistics in 2005 under the supervision of Stephen Fienberg at Carnegie Mellon University and did not leave. Before joining UT Austin in 2023, I was a Dean's Chair Professor in the Department of Statistics and Data Science and the Associate Dean of Research in the Dietrich College of Humanities and Social Sciences.

My research interests revolve around the theoretical properties of statistical and machine learning models for high-dimensional data under various structural assumptions, such as sparsity or intrinsic low dimensionality. In my research work, I have investigated a broad range of issues related to the feasibility of statistical inference in a variety of problems, including high-dimensional regression, time series, privacy, categorical data analysis and graphical modeling, statistical network analysis, algebraic statistics, density-based clustering, topological and geometric data analysis, change-point detection, ranking, and reinforcement learning. Though predominantly of theoretical nature, my research work is motivated by highly practical problems in data science and has direct methodological implications, as it aims at deriving theoretical guarantees in support of existing methods and algorithms.

I am on the editorial board of Foundations and Trend in Statistics. In the past, I served as an AE for Annals of Statistics, Electronic Journal of Statistics, Journal of the American Statistical Association. Journal of Statistical Planning and Inference.

I am an IMS Fellow.