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CONTRIBUTORS.md
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@ -2,34 +2,42 @@ Contributors of DMLC/XGBoost
============================
XGBoost has been developed and used by a group of active community. Everyone is more than welcomed to is a great way to make the project better and more accessible to more users.
Committers
Project Management Committee(PMC)
----------
Committers are people who have made substantial contribution to the project and granted write access to the project.
The Project Management Committee(PMC) consists group of active committers that moderate the discussion, manage the project release, and proposes new committer/PMC members.
* [Tianqi Chen](https://github.com/tqchen), University of Washington
- Tianqi is a Ph.D. student working on large-scale machine learning. He is the creator of the project.
* [Tong He](https://github.com/hetong007), Amazon AI
- Tong is an applied scientist in Amazon AI. He is the maintainer of XGBoost R package.
* [Vadim Khotilovich](https://github.com/khotilov)
- Vadim contributes many improvements in R and core packages.
* [Bing Xu](https://github.com/antinucleon)
- Bing is the original creator of XGBoost Python package and currently the maintainer of [XGBoost.jl](https://github.com/antinucleon/XGBoost.jl).
* [Michael Benesty](https://github.com/pommedeterresautee)
- Michael is a lawyer and data scientist in France. He is the creator of XGBoost interactive analysis module in R.
* [Yuan Tang](https://github.com/terrytangyuan), Ant Financial
- Yuan is a software engineer in Ant Financial. He contributed mostly in R and Python packages.
* [Nan Zhu](https://github.com/CodingCat), Uber
- Nan is a software engineer in Uber. He contributed mostly in JVM packages.
* [Sergei Lebedev](https://github.com/superbobry), Criteo
- Sergei is a software engineer in Criteo. He contributed mostly in JVM packages.
* [Hongliang Liu](https://github.com/phunterlau)
* [Scott Lundberg](http://scottlundberg.com/), University of Washington
- Scott is a Ph.D. student at University of Washington. He is the creator of SHAP, a unified approach to explain the output of machine learning models such as decision tree ensembles. He also helps maintain the XGBoost Julia package.
* [Jiaming Yuan](https://github.com/trivialfis)
- Jiaming contributed to the GPU algorithms. He has also introduced new abstractions to improve the quality of the C++ codebase.
* [Hyunsu Cho](http://hyunsu-cho.io/), Amazon AI
- Hyunsu is an applied scientist in Amazon AI. He is the maintainer of the XGBoost Python package. He also manages the Jenkins continuous integration system (https://xgboost-ci.net/). He is the initial author of the CPU 'hist' updater.
* [Rory Mitchell](https://github.com/RAMitchell), University of Waikato
- Rory is a Ph.D. student at University of Waikato. He is the original creator of the GPU training algorithms. He improved the CMake build system and continuous integration.
* [Hyunsu Cho](http://hyunsu-cho.io/), Amazon AI
- Hyunsu is an applied scientist in Amazon AI. He is the maintainer of the XGBoost Python package. He also manages the Jenkins continuous integration system (https://xgboost-ci.net/). He is the initial author of the CPU 'hist' updater.
* [Jiaming](https://github.com/trivialfis)
- Jiaming contributed to the GPU algorithms. He has also introduced new abstractions to improve the quality of the C++ codebase.
* [Hongliang Liu](https://github.com/phunterlau)
Committers
----------
Committers are people who have made substantial contribution to the project and granted write access to the project.
* [Tong He](https://github.com/hetong007), Amazon AI
- Tong is an applied scientist in Amazon AI. He is the maintainer of XGBoost R package.
* [Vadim Khotilovich](https://github.com/khotilov)
- Vadim contributes many improvements in R and core packages.
* [Bing Xu](https://github.com/antinucleon)
- Bing is the original creator of XGBoost Python package and currently the maintainer of [XGBoost.jl](https://github.com/antinucleon/XGBoost.jl).
* [Sergei Lebedev](https://github.com/superbobry), Criteo
- Sergei is a software engineer in Criteo. He contributed mostly in JVM packages.
* [Scott Lundberg](http://scottlundberg.com/), University of Washington
- Scott is a Ph.D. student at University of Washington. He is the creator of SHAP, a unified approach to explain the output of machine learning models such as decision tree ensembles. He also helps maintain the XGBoost Julia package.
Become a Committer
------------------
@ -91,4 +99,4 @@ List of Contributors
* [Jiaxiang Li](https://github.com/JiaxiangBU)
* [Bryan Woods](https://github.com/bryan-woods)
- Bryan added support for cross-validation for the ranking objective
* [Haoda Fu](https://github.com/fuhaoda)
* [Haoda Fu](https://github.com/fuhaoda)