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Paulo Orenstein

Visiting Professor

IMPA


I'm a visiting professor at IMPA. My research broadly focuses on the interplay between statistics, probability, and computation, particularly as they apply to high-dimensional Bayesian models and Monte Carlo methods. I enjoy working on both theoretical and applied projects, and find them to often illuminate each other.

Before coming to IMPA, I obtained a PhD in Statistics at Stanford University, advised by Persi Diaconis, and received a Masters in Mathematics and BSc in Economics, both from PUC-Rio, in Brazil. I also spent a quarter at Google Research and another at Facebook Reality Labs.

Interests

  • High-dimensional Bayesian Statistics
  • Monte Carlo Methods
  • Probability Theory
  • Applied Statistics and Machine Learning

Education

  • PhD in Statistics, 2019

    Stanford University

  • Masters in Mathematics, 2014

    PUC-Rio

  • BSc in Economics, 2012

    PUC-Rio

Papers

S2S Reboot: an Argument for Greater Inclusion of Machine Learning in Subseasonal to Seasonal Forecasts
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning
When (and How) to Favor Incumbents in Optimal Dynamic Procurement Auctions

Talks

Winsorized Importance Sampling

Theory and results for creating robust importance sampling estimators via winsorization, with finite-sample optimality guarantees.

Forecast Rodeo

Results and award-winning methods of a year-long data challenge to predict the weather 2-6 weeks in advance.

Scalable MCMC for Bayes Shrinkage Priors

How to scale one of the main Bayesian models for sparse high-dimensional regression to hundreds of thousands of predictors.

Codes and Chains

Using Markov chains to decode ciphered messages written in graffiti across the walls of Rio de Janeiro.

Teaching

As an instructor at Stanford University:

  • STATS302: Qualifying Exams Workshop (Probability Theory). Summer 2017.

As a teaching assistant at Stanford University:

  • STATS315B: Modern Applied Statistics II (Graduate). Spring 2018.
  • STATS370: Bayesian Statistics (Graduate). Winter 2018.
  • STATS202: Data Mining and Analysis (Graduate). Fall 2015 and 2017.
  • MATH230B: Theory of Probability II (Graduate). Winter 2017.
  • MATH230A: Theory of Probability I (Graduate). Fall 2016.
  • STATS216: Statistical Learning (Graduate). Fall 2014, Summer 2015 and 2016.
  • STATS160: Statistical Methods (Undergraduate). Spring 2016.
  • STATS200: Statistical Inference (Graduate). Winter 2016.

Contact

  • pauloo@impa.br
  • Estrada Dona Castorina 110, Rio de Janeiro, Brazil, 22460-320