Professor of Biostatistics, New York University
New York, NY
Joined January 2018
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🚀 Exciting news: My new website is live! 🎉 Check it out here: yangfengstat.github.io/ 🌟
P.S. I've been dealing with email glitches lately. If you're waiting for a reply from me and haven’t received it, please drop me a message. Apologies for the hiccup! 🙏
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Yang Feng (冯阳） retweeted
🎓 Call for student posters (high school, undergraduate, graduate) for the inaugural AASF AIX Summit!
⏰ Deadline: February 17, 2026 (AOE)
🔗 bit.ly/aix2026-posters
Yang Feng (冯阳） retweeted
🚀 Call for Papers: Special Issue on Frontiers in Statistical Learning: Data, Networks, and Knowledge Transfer
Journal: Statistical Learning and Data Science (SLADS)
📅 Submission Deadline: March 31, 2026
👨🎓 Guest Editors: Yang Feng, Guangming Pan, Jiaming Xu, Emma Zhang
Join us for SLDS 2026, the flagship conference of the ASA Section on Statistical Learning and Data Science!
📅 Nov 1–3, 2026
📍 Marriott at the Brooklyn Bridge, New York City
🔗 tinyurl.com/SLDS2026📷
@AmstatNews @AmstatLearn @nyupublichealth @NYUDataScience @nyupublichealth
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New paper on causal inference: Design-Based Causal Inference with Missing Outcomes: Missingness Mechanisms, Imputation-Assisted Randomization Tests, and Covariate Adjustment tandfonline.com/doi/full/10.…
@NYUGPHBiostats @nyupublichealth @NYUDataScience @nyulangone
Yang Feng (冯阳） retweeted
CDS-affiliated Professor Yang Feng (@yangfengstat) introduced new algorithms that can control different types of errors independently.
Published in JASA, the work provides tools for applications like loan default prediction where some mistakes matter more than others.
Sharing a new work on Neyman-Pearson classification problem via cost-sensitive learning. @NYUGPHBiostats @nyupublichealth @NYUDataScience
Neyman-Pearson Multi-class Classification via Cost-sensitive Learning: (JASA) tandfonline.com/doi/full/10.…
Sharing a new work on Neyman-Pearson classification problem via cost-sensitive learning. @NYUGPHBiostats @nyupublichealth @NYUDataScience
Neyman-Pearson Multi-class Classification via Cost-sensitive Learning: (JASA) tandfonline.com/doi/full/10.…
Thrilled to receive the 2024 NYU GPH Teaching Excellence Award. Many thanks to my students for your support and nomination! @NYUGPHBiostats @nyupublichealth
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🎉 Super excited to share that our paper “Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms” (arxiv.org/abs/2310.15330) was accepted to #ICML2024
@nyupublichealth @NYUGPHBiostats @NYUDataScience
New manuscript "Unsupervised Federated Learning: A Federated Gradient EM Algorithm for Heterogeneous Mixture Models with Robustness against Adversarial Attacks" #MachineLearning #DataScience #adversarial #federatedlearning
arxiv.org/abs/2310.15330
Oct 26 at 9pm EST, I will host an information session over Zoom on the Ph.D. in Public Health with Biostatistics concentration at NYU. @NYUGPHBiostats @nyupublichealth @NYUDataScience
Register Below:
nyu.zoom.us/meeting/register…
New work accepted by JASA @NYUGPHBiostats @nyupublichealth @NYUDataScience
PCABM: Pairwise Covariates-Adjusted Block Model for Community Detection tandfonline.com/doi/full/10.…
Yang Feng (冯阳） retweeted
A @Patterns_CP paper by @LijiaW0206 @xtong001 discovered the impacts of statistics on scientific disciplines over the recent decades and provided a dataset (zenodo.org/record/6565329) for citation network analysis.
cell.com/patterns/fulltext/S… #Statistics #DataScience #ScienceImpact
🎉 Thrilled and honored to be elected as a 2023 IMS Fellow! A heartfelt thank you to my incredible mentors, dedicated collaborators, and inspiring students for their unwavering support on this journey. Your collective wisdom has made this achievement possible. 🙏
2023 IMS Fellows
Each Fellow has exhibited exceptional prowess in statistical or probabilistic research or has showcased remarkable leadership that has left a lasting impact on the field.
imstat.org/2023/05/02/2023-i…
Post-doc opening on machine learning and general data science. Deadline: May 15. Welcome to apply or retweet! Thanks! @nyupublichealth @NYUGPHBiostats @NYUDataScience @SLDS_ASA #DataScience #MachineLearning
apply.interfolio.com/104510
