School of Humanities and Sciences
Showing 101-200 of 215 Results
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Percy Liang
Associate Professor of Computer Science and, by courtesy, of Statistics
BioPercy Liang is an Associate Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011). His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers easier to communicate with through natural language. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), and a Microsoft Research Faculty Fellowship (2014).
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Scott W Linderman
Assistant Professor of Statistics and, by courtesy, of Computer Science and of Electrical Engineering
BioScott is an Assistant Professor of Statistics and, by courtesy, Electrical Engineering and Computer Science at Stanford University. He is also an Institute Scholar in the Wu Tsai Neurosciences Institute and a member of Stanford Bio-X and the Stanford AI Lab. His lab works at the intersection of machine learning and computational neuroscience, developing statistical methods to analyze large scale neural data. Previously, Scott was a postdoctoral fellow with Liam Paninski and David Blei at Columbia University, and he completed his PhD in Computer Science at Harvard University with Ryan Adams and Leslie Valiant. He obtained his undergraduate degree in Electrical and Computer Engineering from Cornell University and spent three years as a software engineer at Microsoft before graduate school.
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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
Robert and Barbara Kleist Professor in the School of Engineering and Professor of Statistics and, by courtesy, of Mathematics
On Leave from 06/10/2022 To 06/30/2023BioI 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. -
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
Assistant 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
Current Research and Scholarly Interestsstatistical computational biology focusing on splicing, cancer and microbes
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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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Laura Symul
Research Scientist
BioLaura Symul has obtained her PhD in computational biology from the École Polytechnique Fédérale de Lausanne (EPFL), in Switzerland, where she has worked on the molecular regulation of the circadian clock. In particular she explored the regulation of rhythmic gene expression and protein translation combining analyses of -omics data with mathematical models describing the regulatory dynamics to infer quantities otherwise not measurable.
Laura Symul has also specialized in the visualization of data and, during her industry experience, has helped companies to take data-driven decisions.
As a postdoctoral fellow, her research focuses on women's health and menstrual health in particular. This includes research on fertility, on cycle-related symptoms and on drivers of changes in vaginal microbiome communities. She uses a combination of self-tracked data from mobile phone apps and devices and clinical multi-omics data. -
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.
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Lu Tian
Professor of Biomedical Data Science and, by courtesy, of Statistics
Current Research and Scholarly InterestsMy research interest includes
(1) Survival Analysis and Semiparametric Modeling;
(2) Resampling Method ;
(3) Meta Analysis ;
(4) High Dimensional Data Analysis;
(5) Precision Medicine for Disease Diagnosis, Prognosis and Treatment. -
Robert Tibshirani
Professor of Biomedical Data Science and of Statistics
Current Research and Scholarly InterestsMy research is in applied statistics and biostatistics. I specialize in computer-intensive methods for regression and classification, bootstrap, cross-validation and statistical inference, and signal and image analysis for medical diagnosis.
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Marius Aurel Tirlea
Ph.D. Student in Statistics, admitted Autumn 2018
Ph.D. Minor, EconomicsBioI am a fifth-year PhD student in the Statistics department at Stanford University, where I have the privilege of being advised by Professor Joseph Romano. My research is mainly centered on developing nonparametric hypothesis tests, primarily with application to time series data.
Prior to attending Stanford, I received my Bachelor's and Master's degrees in Mathematics from Trinity College, University of Cambridge. -
Guenther Walther
Professor of Statistics
BioGuenther Walther studied mathematics, economics, and computer science at the University of Karlsruhe in Germany and received his Ph.D. in Statistics from UC Berkeley in 1994.
His research has focused on statistical methodology for detection problems, shape-restricted inference, and mixture analysis, and on statistical problems in astrophysics and in flow cytometry.
He received a Terman fellowship, a NSF CAREER award, and the Distinguished Teaching Award of the Dean of Humanities and Sciences at Stanford. He has served on the editorial boards of the Journal of Computational and Graphical Statistics, the Journal of the Royal Statistical Society, the Annals of Statistics, the Annals of Applied Statistics, and Statistical Science. He was program co-chair of the 2006 Annual Meeting of the Institute of Mathematical Statistics and served on the executive committee of IMS from 1998 to 2012. -
Wing Hung Wong
Stephen R. Pierce Family Goldman Sachs Professor of Science and Human Health and Professor of Biomedical Data Science
Current Research and Scholarly InterestsCurrent interest centers on the application of statistics to biology and medicine. We are particularly interested in questions concerning gene regulation, genome interpretation and their applications to precision medicine.
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Zifei Xu
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2021
Course Grader, StatisticsBioStudent in Master of Computational & Mathematical Engineering, Data Science Track
