Biography
Yang Feng is an associate professor of biostatistics in the School of Global Public Health at New York University.
Feng focuses on developing and applying machine learning methods in public health, high-dimensional data analysis, network models, nonparametric and semiparametric methods, and bioinformatics. He also leads the Feng Lab.
Info
- Post-Doctoral Associate in Biostatistics:
The Department of Biostatistics at the NYU School of Global Public Health is seeking candidates with a Ph.D. in Statistics/Biostatistics, Computer Science, or related fields for an exciting full-time Post-Doctoral Associate position available beginning on June 1 or Sep 1, 2022, working with Dr. Yang Feng and Dr. Rebecca Betensky.
The postdoc associate will work to:
- Develop novel machine learning methods and their associate theory.
- Apply existing and new machine learning methods to public health and medical data.
- Develop companion software.
Please apply via Interfolio here.
He has published papers in Annals of Statistics, Annals of Applied Statistics, Biometrika, IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Royal Statistical Society Series B, Journal of the American Statistical Association, Journal of Machine Learning Research, Science Advances, Journal of Econometrics, Journal of Business & Economic Statistics, etc.
He is currently an associate editor for
- Journal of the American Statistical Association
- Journal of Business & Economic Statistics
- Statistica Sinica
- Stat
- Statistical Analysis and Data Mining: The ASA Data Science Journal.
His research is partially supported by
- NSF CAREER Grant DMS-2013789: CAREER: Statistical inference of network and relational data
- NSF Grant 2034022: RAPID: Behavioral Epidemic Modeling For COVID-19 Containment
- NIH 1R21AG074205-01: Multiclass classification under prioritized error control and specific error costs with applications to dementia classification
My Google Scholar Page ( By Year)
Open Positions and Opportunities:
- Research Assistant:
Feng Lab is continuously looking for talents at undergraduate, master and Ph.D. level. If you are interested, please submit an application at https://bit.ly/2KMEflH.
Interests
- Machine learning in public health
- High-dimensional statistics
- Network models
- Nonparametric and semiparametric methods
- Bioinformatics
Education
-
PhD in Operations Research, 2010
Princeton University
-
BS in Mathematics, 2006
University of Science and Technology of China (USTC)
