# Researchers in Applied & Theoretical Statistics

## Faculty

Researcher | Title | Research Focus | Research Interests |
---|---|---|---|

Peter Bartlett | Professor | Machine Learning | |

Peter Bickel | Professor Emeritus & Professor in the Graduate School | ||

David R Brillinger | Professor | Applied Statistics, Bioinformatics/Biostatistics, Statistics in Physical Sciences, Theory of Statistics | Random process theory and data analysis, risk analysis, spatial-temporal trajectory modeling, sports statistics, applications to ecology, forestry, marine biology, neuroscience, seismology and engineering. |

Ching-Shui Cheng | Professor Emeritus | ||

Alex D'Amour | Neyman Visiting Assistant Professor | Applied Statistics, Bayesian Statistics, Machine Learning, Statistics in Social Sciences, Theory of Statistics | |

Peng Ding | Assistant Professor | Applied Statistics, Bioinformatics/Biostatistics, Bayesian Statistics, Statistics in Social Sciences | causal inference in experiments and observational studies, missing data |

Sandrine Dudoit | Professor | Applied Statistics, Bioinformatics/Biostatistics | |

Noureddine El Karoui | Professor | Applied Statistics, Theory of Statistics | High-dimensional statistics, random matrices, high-dimensional robust regression, high-dimensional M-estimation, the bootstrap and resampling in high-dimension, limit theorems and statistical inference, applied statistics |

Avi Feller | Assistant Professor | Applied Statistics, Bayesian Statistics, Machine Learning, Statistics in Social Sciences | |

Will Fithian | Assistant Professor | ||

Lisa Goldberg | Adjunct Professor | Applied Statistics, Bayesian Statistics, Statistics in Social Sciences, Theory of Statistics | Financial economics, statistical evaluation of investment strategies, asset allocation, credit and counterparty risk, socially responsible investing |

Adityanand Guntuboyina | Assistant Professor | ||

Haiyan Huang | Associate Professor | Applied Statistics, Bioinformatics/Biostatistics | High dimensional and integrative genomic data analysis; Network modeling;Hierarchical multi-label classification; translational bioinformatics |

Nicholas P. Jewell | Professor | Bioinformatics/Biostatistics | Infectious diseases, specifically HIV; chronic disease epidemiology; envionmental epidemiology; survival analysis; human rights statistics |

Michael Jordan | Professor | ||

Cari Kaufman | Lecturer | Bayesian Statistics, Statistics in Physical Sciences | spatial and environmental statistics; statistical modeling incorporating computer simulators of physical processes |

Oscar Madrid Padilla | Neyman Visiting Assistant Professor | Applied Statistics, Bayesian Statistics, Machine Learning, Theory of Statistics | |

Jon McAuliffe | Adjunct Associate Professor | Applied Statistics, Machine Learning, Statistics in Physical Sciences | machine learning, statistical prediction, variational inference, statistical computing, optimization |

Rasmus Nielsen | Professor | Bioinformatics/Biostatistics | Statistical Genomics, Theoretical Population Genetics |

Deborah Nolan | Professor and Chair | ||

Christopher Paciorek | Adjunct Professor | Applied Statistics, Bayesian Statistics | environmental statistics, statistical computing, spatial statistics, Bayesian statistics |

Sam Pimentel | Assistant Professor | Applied Statistics, Bioinformatics/Biostatistics, Statistics in Social Sciences | |

Elizabeth Purdom | Associate Professor | Applied Statistics, Bioinformatics/Biostatistics | |

John Rice | Professor Emeritus | ||

Gaston Sanchez | Lecturer | Applied Statistics, Statistics in Social Sciences | Dimension reduction techniques and component-based methods |

Jasjeet Sekhon | Professor | Applied Statistics, Statistics in Social Sciences | |

Juliet Shaffer | Teaching Professor Emerita | ||

Yun S. Song | Professor | Bioinformatics/Biostatistics, Machine Learning | Computational biology, statistical genetics, applied probability |

Terry Speed | Professor Emeritus | Bioinformatics/Biostatistics | The application of statistics to genetics and genomics, and to related fields such as proteomics, metabolomics and epigenomics. |

Philip B. Stark | Professor | Applied Statistics, Statistics in Physical Sciences, Statistics in Social Sciences | uncertainty quantification and inference, inverse problems, nonparametrics, risk assessment, earthquake prediction, election auditing, geomagnetism, cosmology, litigation, food/nutrition |

Chuck Stone | Professor Emeritus | The stability and sustainability of the worldwide economy in the first half of the twenty-first century and, especially, its lack thereof. One possible result of unsustainability is a transition to a decent sustainable state; another is collapse. | |

Bernd Sturmfels | Professor | Algebraic Statistics | |

Aram Thomasian | Professor Emeritus | ||

Mark van der Laan | Professor | ||

Ken Wachter | Professor | Statistics in Social Sciences | Mathematical demography, models for the evolution of aging, simulation. |

Martin Wainwright | Professor | ||

Bin Yu | Professor | Applied Statistics, Bioinformatics/Biostatistics, Machine Learning, Theory of Statistics | Statistical inference for high dimensional data and interdisciplinary research in neuroscience, remote sensing, and text summarization. |

## Visitors

Researcher | Title | Research Focus | Research Interests |
---|---|---|---|

Yanyan Lan | Visiting Scholar | Machine Learning | information retrieval, natural language processing |

## Postdocs

Researcher | Title | Research Focus | Research Interests |
---|---|---|---|

Nicholas Michaud | Postdoctoral Scholar (joint ESPM) | Applied Statistics, Bayesian Statistics | |

Aaditya Ramdas | Postdoctoral Scholar | Machine Learning, Theory of Statistics | |

Shusen Wang | Postdoc | Machine Learning | machine learning, randomized numerical linear algebra |

## Graduate Students

Researcher | Dissertation | Advisor | Research Focus |
---|---|---|---|

Nicholas Altieri | Machine Learning | ||

Rebecca Barter | Bin Yu | ||

Eli Ben-Michael | Applied Statistics, Machine Learning, Statistics in Social Sciences | ||

Jade Benjamin-Chung | Bioinformatics/Biostatistics | ||

Joseph Borja | Martin Wainwright and Michael Jordan | ||

Emily Chang | Bioinformatics/Biostatistics | ||

Kathryn (Benton) Colborn | Statistical models for longitudinal analysis of single and mixed species infections | Terry Speed | Bioinformatics/Biostatistics |

Jeremy Coyle | Alan Hubbard | Bioinformatics/Biostatistics | |

Anna Decker | Semiparametric, prediction, variable importance, and longitudinal causal effect estimation in critical care | Alan Hubbard | Bioinformatics/Biostatistics, Machine Learning |

Stephanie DeGraaf | Elizabeth Purdom | Bioinformatics/Biostatistics | |

Iván Díaz | Causal inference methods for continuous exposures | Mark van der Laan | Bioinformatics/Biostatistics, Machine Learning, Theory of Statistics |

Keenan Fenton | Bioinformatics/Biostatistics | ||

Arturo Fernandez | Jon McAuliffe and Philip Stark | Applied Statistics, Machine Learning, Statistics in Physical Sciences | |

Jonathan Fischer | Yun S. Song | Applied Statistics, Bioinformatics/Biostatistics, Machine Learning | |

Ryan Giordano | Michael Jordan | Applied Statistics, Bayesian Statistics, Machine Learning, Statistics in Physical Sciences | |

Geno Guerra | Rasmus Nielsen | Applied Statistics, Bioinformatics/Biostatistics | |

Curt Hansen | Sandrine Dudoit | Bioinformatics/Biostatistics, Machine Learning | |

Chun Yu Hong (Johnny) | Will Fithian and Perry de Valpine | Applied Statistics, Bioinformatics/Biostatistics | |

Steve Howard | Jasjeet Sekhon & Jon McAuliffe | ||

Miyabi Ishihara | |||

Marla Johnson | Elizabeth Purdom | Bioinformatics/Biostatistics | |

Sören Künzel | Bickel, Sekhon, Yu | Applied Statistics, Machine Learning, Statistics in Social Sciences, Theory of Statistics | |

Karl Kumbier | Bin Yu | Applied Statistics, Bioinformatics/Biostatistics, Machine Learning | |

Lihua Lei | |||

Sam Lendle | Mark van der Laan | Bioinformatics/Biostatistics | |

Jingyi Jessica Li | Statistical Methods for Analyzing High-Throughput Genomic Data | Peter J. Bickel & Haiyan Huang | Bioinformatics/Biostatistics |

Runjing (Bryan) Liu | Applied Statistics, Bayesian Statistics, Machine Learning | ||

Kevin McLoughlin | Modeling and Analysis of Oligonucleotide Microarray Data for Pathogen Detection | Terry Speed | Bioinformatics/Biostatistics, Machine Learning |

Jarrod Millman | Bioinformatics/Biostatistics | ||

Soumendu Sundar Mukherjee | |||

Jamie Murdoch | Bin Yu | Machine Learning | |

Kellie Ottoboni | Philip Stark | ||

Lucia Petito | Bioinformatics/Biostatistics | ||

Yannik Pitcan | Peter Bartlett | Bayesian Statistics, Machine Learning | |

Steven Pollack | Bioinformatics/Biostatistics | ||

Sujayam Saha | Bin Yu, Aditya Guntuboyina | Machine Learning, Theory of Statistics | |

Oleg Sofrygin | Causal Inference | Mark van der Laan | Bioinformatics/Biostatistics |

Jake Soloff | Bayesian Statistics, Machine Learning, Theory of Statistics | ||

Sara Stoudt | Will Fithian and Perry de Valpine | ||

Kelly Street | Sandrine Dudoit | Applied Statistics, Bioinformatics/Biostatistics | |

Vanessa Viggiano | Bioinformatics/Biostatistics | ||

Yu Wang | Machine Learning, Theory of Statistics | ||

Andre Kurepa Waschka | Alan Hubbard and Mark van der Laan | Bioinformatics/Biostatistics | |

Yuting Wei | Martin Wainwright, Adityanand Guntuboyina | Machine Learning, Theory of Statistics | |

Chelsea Zhang | Bayesian Statistics, Machine Learning |