move contributions to thanks

README.md

@@ -172,30 +172,3 @@ Data-centric AI is still growing, and we want to capture emerging trends as they
 
 Data-centric approaches have had a wide-ranging impact wherever machine learning is used and deployed, whether in academia, industry or other organizations. Impact spans modalities such as structured data, text, images, videos, graphs and others, while areas include text and image processing, medical imaging, computational biology, autonomous driving, etc.
 
-
-# Contributors
-
-This GitHub is maintained by [Karan Goel](https://krandiash.github.io) and [Laurel Orr](https://cs.stanford.edu/people/lorr1/) from [Hazy Research](https://hazyresearch.stanford.edu). Reach out to kgoel [at] cs [dot] stanford [dot] edu for questions, comments and feedback.
-
-
-The following individuals and organizations have contributed to the development of this GitHub so far,
-- [Kabir Goel](https://kabirgoel.com) created the header artwork.
-- Members of [Hazy Research](https://hazyresearch.stanford.edu) created the first version of this resource,
-    - [Michael Zhang](https://michaelzhang.xyz) (Robustness)
-    - [Mayee Chen](https://mayeechen.github.io) (Data Programming, Weak Supervision)
-    - [Maya Varma](https://maya-varma.com) (Computational Biology)
-    - [Sabri Eyuboglu](https://seyuboglu.com) (Computational Biology, Interactive ML)
-    - [Megan Lesczynski](http://www.mleszczy.com/) (Named Entity Linking)
-    - Avanika Narayan (Benchmarking)
-    - [Dan Fu](http://www.danfu.org/) (Contrastive Learning)
-    - [Arjun Desai](https://scholar.google.com/citations?user=0tusMC4AAAAJ&hl=en) (Medical Imaging)
-    - [Tri Dao](https://stanford.edu/~trid/) (Augmentation)
-    - [Khaled Saab](https://web.stanford.edu/~ksaab/) (Observational Supervision)
-    - [Sen Wu](https://stanford.edu/~senwu/) (Augmentation)
-    - [Piero Molino](https://w4nderlu.st/about) (Editing)
-    - [Beidi Chen](https://www.cs.rice.edu/~bc20/) (Sparsity)
-- [Braden Hancock](https://www.bradenhancock.com) from [Snorkel.ai](https://snorkel.ai) contributed to weak supervision
-- [Jared Dunnmon](https://jdunnmon.github.io) from the Defense Innovation Unit edited multiple sections
-- Alvin Ming and [Sharon Li](http://pages.cs.wisc.edu/~sharonli/) from U-Wisconsin contributed work in outlier detection
-- [Ce Zhang](https://scholar.google.ch/citations?user=GkXqbmMAAAAJ&hl=en) and [Cedric Renggli](https://people.inf.ethz.ch/rengglic/) from ETH-Zurich added discussion for data cleaning and MLOps
-- [Eugene Wu](http://www.cs.columbia.edu/~ewu/) from Columbia added discussion for data cleaning

THANKS.md

@@ -0,0 +1,18 @@
+# Contributors
+
+This GitHub is maintained by [Karan Goel](https://krandiash.github.io) and [Laurel Orr](https://cs.stanford.edu/people/lorr1/) from [Hazy Research](https://hazyresearch.stanford.edu). Reach out to kgoel [at] cs [dot] stanford [dot] edu for questions, comments and feedback.
+
+
+The following individuals and organizations have contributed to the development of this GitHub so far,
+- [Kabir Goel](https://kabirgoel.com) created the header artwork.
+- Members of [Hazy Research](https://hazyresearch.stanford.edu) created the first version of this resource, including
+[Michael Zhang](https://michaelzhang.xyz), [Mayee Chen](https://mayeechen.github.io), [Maya Varma](https://maya-varma.com),, [Sabri Eyuboglu](https://seyuboglu.com), [Megan Lesczynski](http://www.mleszczy.com/), Avanika Narayan, [Dan Fu](http://www.danfu.org/), [Arjun Desai](https://scholar.google.com/citations?user=0tusMC4AAAAJ&hl=en), [Tri Dao](https://stanford.edu/~trid/), [Khaled Saab](https://web.stanford.edu/~ksaab/), [Sen Wu](https://stanford.edu/~senwu/), [Beidi Chen](https://www.cs.rice.edu/~bc20/)
+- [Piero Molino](https://w4nderlu.st/about) from [Predibase](https://predibase.com) added discussion around declarative machine learning
+- [Braden Hancock](https://www.bradenhancock.com) from [Snorkel.ai](https://snorkel.ai) contributed to weak supervision
+- [Jared Dunnmon](https://jdunnmon.github.io) from the Defense Innovation Unit edited multiple sections
+- Alvin Ming and [Sharon Li](http://pages.cs.wisc.edu/~sharonli/) from U-Wisconsin contributed work in outlier detection
+- [Ce Zhang](https://scholar.google.ch/citations?user=GkXqbmMAAAAJ&hl=en) and [Cedric Renggli](https://people.inf.ethz.ch/rengglic/) from ETH-Zurich added discussion for data cleaning and MLOps
+- [Eugene Wu](http://www.cs.columbia.edu/~ewu/) from Columbia added discussion for data cleaning
+- [Cody Coleman](http://www.codycoleman.com) from Stanford added discussion for data selection
+
+Thanks to everyone who has provided feedback on this resource, including Dan Hendrycks and Jacob Steinhardt at UC-Berkeley, James Zou, Matei Zaharia, Daniel Kang, Chelsea Finn from Stanford, Mike Cafarella from MIT, Ameet Talkwalkar from CMU.