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Yang Feng

Yang Feng

Yang Feng

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Professor of Biostatistics

Professional overview

Yang Feng is a Professor and Ph.D. Program Director of Biostatistics in the School of Global Public Health and an affiliate faculty in the Center for Data Science at New York University. He obtained his Ph.D. in Operations Research at Princeton University in 2010.

Feng's research interests encompass the theoretical and methodological aspects of machine learning, high-dimensional statistics, social network models, and nonparametric statistics, leading to a wealth of practical applications, including Alzheimer's disease, cancer classification, and electronic health records. His research has been funded by multiple grants from the National Institutes of Health (NIH) and the National Science Foundation (NSF), notably the NSF CAREER Award.

He is currently an Associate Editor for the Journal of the American Statistical Association (JASA), the Journal of Business & Economic Statistics (JBES), Journal of Computational & Graphical Statistics (JCGS), and the Annals of Applied Statistics (AoAS). His professional recognitions include being named a fellow of the American Statistical Association (ASA) and the Institute of Mathematical Statistics (IMS), as well as an elected member of the International Statistical Institute (ISI).

Please visit Dr. Yang Feng's website and Google Scholar page from more information.

Education

B.S. in Mathematics, University of Science and Technology of China, Hefei, China
Ph.D. in Operations Research, Princeton University, Princeton, NJ

Areas of research and study

Bioinformatics
Biostatistics
High-dimensional data analysis/integration
Machine learning
Modeling Social and Behavioral Dynamics
Nonparametric statistics

Publications

Publications

Clinical, Pathological, and Molecular Characteristics of Diffuse Spinal Cord Gliomas

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Community detection with nodal information : Likelihood and its variational approximation

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Differential Role of Hyperglycemia on Survival in IDH-wildtype Glioblastoma Subclasses

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Discussion of “Cocitation and Coauthorship Networks of Statisticians”

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Large-scale model selection in misspecified generalized linear models

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Model Averaging for Nonlinear Regression Models

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Spectral clustering via adaptive layer aggregation for multi-layer networks

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Targeting predictors via partial distance correlation with applications to financial forecasting

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Testing community structure for hypergraphs

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Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models

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A demonstration of the RaSEn package

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Analytical performance of lateral flow immunoassay for SARS-CoV-2 exposure screening on venous and capillary blood samples

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Association of body composition parameters measured on CT with risk of hospitalization in patients with Covid-19

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Comparison of solid tissue sequencing and liquid biopsy accuracy in identification of clinically relevant gene mutations and rearrangements in lung adenocarcinomas

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Imbalanced classification: A paradigm-based review

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Mediation effect selection in high-dimensional and compositional microbiome data

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NCOG-11. ASSOCIATION OF HYPERGLYCEMIA AND TUMOR SUBCLASS ON SURVIVAL IN IDH-WILDTYPE GLIOBLASTOMA

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Neyman-Pearson Multi-class Classification via Cost-sensitive Learning

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RaSE: A Variable Screening Framework via Random Subspace Ensembles

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RaSE: Random Subspace Ensemble Classification

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Super RaSE: Super Random Subspace Ensemble Classification

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Targeted crisis risk control: A neyman-pearson approach

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The Interplay of Demographic Variables and Social Distancing Scores in Deep Prediction of US COVID-19 Cases

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Visceral adipose tissue in patients with COVID-19: risk stratification for severity

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A Projection Based Conditional Dependence Measure with Applications to High-dimensional Undirected Graphical Models

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Contact

yang.feng@nyu.edu 708 Broadway New York, NY, 10003