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
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.…
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
Yang Feng (冯阳) retweeted
The first PQAR info session will take place on Tuesday, 9/20 at 8:30 pm ET !
RSVP here:
nyu.zoom.us/j/96196956201
#PQAR #NYU #NYC #Biostats #aging #NIH #NIA #AcademicTwitter #statstwitter #REU #datascience #STEM #diversityinSTEM #publichealth #stats #R #Epidemiology #Computing
Yang Feng (冯阳) retweeted
Happening now!
2022 Workshop on Statistical Network Analysis and Beyond @nyupublichealth
yangfeng.hosting.nyu.edu/sna…
Yang Feng (冯阳) retweeted
IMS Co-Sponsored Meeting
2022 Workshop on Statistical Network Analysis and Beyond
August 3–5, 2022, New York, USA
yangfeng.hosting.nyu.edu/sna…
@yangfengstat
Yang Feng (冯阳) retweeted
On Monday, 10/18 at 8:00 pm, Dr.@yangfengstat will host an info session on our doctoral program!
Join the conversation here: apply.publichealth.nyu.edu/r…
#biostatistics #diversity #datascience #NYU #PhD #stat #PhD #statstwitter #academictwitter #STATS #publichealth #NYC
Yang Feng (冯阳) retweeted
📢📢📢We are hiring!
Please apply for Visiting Assistant Professor at
apply.interfolio.com/86357 and Visiting Associate Professor at apply.interfolio.com/86359
@nyupublichealth @nyuniversity
#STEM #hiring #AcademicTwitter
Yang Feng (冯阳) retweeted
📢📢📢We've created a brand new certificate for non-NYU students! The Advanced Certificate in Public Health Data Science, provides training in Biostats, Epi and public health.
Click here to learn more: publichealth.nyu.edu/program…
Yang Feng (冯阳) retweeted
Replying to @NYGovCuomo @HealthNYGov
Statistical evidence as follows. #SocialDistancing
nydailynews.com/opinion/ny-o…
Yang Feng (冯阳) retweeted
OPINION: Has social distancing slowed down coronavirus spread? The evidence so far looks promising.
trib.al/lS9vJEY
Yang Feng (冯阳) retweeted
BREAKING: Multiple members of the Tisch School of the Arts community have tested positive for COVID-19, according to an email sent to the school today by Dean Allyson Green. The rest of the NYU community has not yet been notified. Article to come.
Yang Feng (冯阳) retweeted
We developed the NP-ROC band, whose x axis shows varying desirable thresholds on the population type I error: bit.ly/2MtsbVo xitter.cf/enricocoiera/status/10…
Benchmarking machine learning often relies on AUC, but real world performance happens over a small portion of the ROC. So AUC might be a good general purpose metric for model development but is not a clinically useful one.
link.springer.com/article/10…
whoi.edu/cms/files/Global_Ec…
Yang Feng (冯阳) retweeted
A cartoon video illustrating the basic ideas behind the NP classification: youtube.com/watch?v=vbeeHqJ_…
Yang Feng (冯阳) retweeted
Our recent article on Science Advances about an umbrella algorithm to implement general binary classification algorithms the Neyman-Pearson (NP) paradigm, which aims to control the type I error under a pre-specified threshold with high probability: advances.sciencemag.org/cont…
















