Stanford University
Showing 101-150 of 188 Results
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Qiao Liu
Postdoctoral Scholar, Statistics
BioI am currently a postdoctoral scholar at the Department of Statistics, Stanford University, advised by Prof. Wing Hung Wong (NAS member). Prior to that, I was a PhD student at Tsinghua University, where I spent two years at Stanford University, jointly advised by Prof. Wing Hung Wong. My research interests lie in the intersection of machine learning, statistics, and computational biology. I'm especially fascinated by solving several problems in statistics, such as density estimation, causal inference, and likelihood-free Bayesian, with deep generative models. Besides, I'm also interested in various problems in computational biology and biomedical informatics, which involve genomic data, pharmacology data, and biomedical data analysis.
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Andrea Montanari
John D. and Sigrid Banks Professor and Professor of Mathematics
BioI am interested in developing efficient algorithms to make sense of large amounts of noisy data, extract information from observations, estimate signals from measurements. This effort spans several disciplines including statistics, computer science, information theory, machine learning.
I am also working on applications of these techniques to healthcare data analytics. -
Tim Morrison
Ph.D. Student in Statistics, admitted Autumn 2020
BioI am a fourth-year PhD student in Statistics. I am fortunate to be advised by Professor Art Owen and also to work with Professor Mike Baiocchi. I am also grateful to have received the B. C. and E. J. Eaves Stanford Graduate Fellowship. My research interests include constrained experimental design and causal inference.
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Art Owen
Max H. Stein Professor
Current Research and Scholarly InterestsStatistical methods to analyze large data matrices in bioinformatics
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Julia Palacios
Associate Professor of Statistics, of Biomedical Data Science and, by courtesy, of Biology
BioDr. Palacios seek to provide statistically rigorous answers to concrete, data driven questions in evolutionary genetics and public health . My research involves probabilistic modeling of evolutionary forces and the development of computationally tractable methods that are applicable to big data problems. Past and current research relies heavily on the theory of stochastic processes, Bayesian nonparametrics and recent developments in machine learning and statistical theory for big data.
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Joseph Romano
Professor of Statistics and of Economics
Current Research and Scholarly InterestsWork in progress is described under "Projects"
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Chiara Sabatti
Professor of Biomedical Data Science and of Statistics
Current Research and Scholarly InterestsStatistical models and reasoning are key to our understanding of the genetic basis of human traits. Modern high-throughput technology presents us with new opportunities and challenges. We develop statistical approaches for high dimensional data in the attempt of improving our understanding of the molecular basis of health related traits.
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Julia Salzman
Associate Professor of Biomedical Data Science, of Biochemistry and, by courtesy, of Statistics and of Biology
Current Research and Scholarly Interestsstatistical computational biology focusing on splicing, cancer and microbes
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Timothy Sudijono
Ph.D. Student in Statistics, admitted Autumn 2021
BioI'm a third year PhD student advised by Sourav Chatterjee. My research interests are in causal inference, neural networks, and probability theory.
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Paul Switzer
Professor of Statistics and of Environmental Earth System Science, Emeritus
BioDr. Switzer's research interests are in the development of statistical tools for the environmental sciences. Recent research has focused on the interpretation of environmental monitoring data, design of monitoring networks, detection of time trends in environmental and climatic paramenters, modeling of human exposure to pollutants, statistical evaluation of numerical climate models and error estimation for spatial mapping.
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Hua Tang
Professor of Genetics and, by courtesy, of Statistics
Current Research and Scholarly InterestsDevelop statistical and computational methods for population genomics analyses; modeling human evolutionary history; genetic association studies in admixed populations.
