codalab · ihsaan-ullah · Dec 23, 2025
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+# About CodaLab
+
+CodaLab is an open-source platform that provides an ecosystem for conducting computational research in a more efficient, reproducible, and collaborative manner.
+
+**CodaLab Worksheets** allow you to capture complex research pipelines in a reproducible way and create "executable papers". Use any data format or programming language — great for the power user! CodaLab worksheets has a [public instance](https://worksheets.codalab.org/) hosted by Stanford University.
+
+**CodaLab Competitions** bring together the entire community to tackle the most challenging data and computational problems today. You can win prizes and also create your own competition. CodaLab Competitions has a [public instance](https://codalab.lisn.fr/) hosted by Université Paris-Saclay. [Click here](https://github.com/codalab/codalab-competitions/wiki/Statistics-of-the-public-servers) for statistics about the growth and activity of the public servers.
+
+**CodaBench** offers hosting competitions and benchmarks on virtually any data science problem. Building upon the capabilities of CodaLab Competitions, it introduces additional features and enhanced performance. Codabench has a [public instance](https://www.codabench.org/) hosted by Université Paris-Saclay. The code is [open-source](https://github.com/codalab/codabench).
+
+# The CodaLab Team
+
+### Governance
+
+<table>
+  <tr>
+    <td width="200px"><img src="https://github.com/codalab/codalab-competitions/wiki/images/percy.jpeg" alt="" style="max-width:100%;"></td>
+    <td><p><a href="http://cs.stanford.edu/%7Epliang/">Percy Liang</a> is an assistant professor of Computer Science at Stanford University. His primary research areas are machine learning and natural language processing.  He leads the development of CodaLab in close collaboration with Microsoft Research and the rest of the community.</p></td>
+  </tr>
+
+  <tr>
+    <td width="200px"><img src="https://github.com/codalab/codalab-competitions/wiki/images/isabelle.png" alt="" style="max-width:100%;"></td>
+    <td><p><a href="http://www.clopinet.com/isabelle/">Isabelle Guyon</a> is full professor at UPSud University Paris-Saclay and president of ChaLearn a non-profit organization dedicated to running machine learning competitions. Her research interested include automatic machine learning, transfer learning, and causal discovery. Isabelle served as an advisor in the development of the CodaLab competition platform and pioneered the implementation of several challenges on CodaLab.</p></td>
+  </tr>
+
+  <tr>
+    <td width="200px"><img src="https://github.com/codalab/codalab-competitions/wiki/images/EvelyneViegas.jpg" alt="" style="max-width:100%;"></td>
+    <td><p><a href="http://research.microsoft.com/~evelynev/">Evelyne Viegas</a> is a Director at Microsoft Research responsible for the outreach artificial intelligence program. She leads the CodaLab project working in collaboration with Isabelle Guyon, Percy Liang and the machine learning and artificial intelligence communities.</p></td>
+  </tr>
+
+  <tr>
+    <td width="200px"><img src="images/sergio_escalera.jpg" alt="Sergio Escalera" style="max-width:100%;"></td>
+    <td><p><a href="http://sergioescalera.com/">Sergio Escalera</a>  is adjunct professor at Universitat Oberta de Catalunya, Aalborg University, and Dalhousie University and a member of the Visual and Computational Learning consolidated research group of Catalonia and a member of the Computer Vision Center at UAB. He is series editor of The Springer Series on Challenges in Machine Learning. He is Editor-in-Chief of American Journal of Intelligent Systems and editorial board member of more than 5 international journals. He is vice-president of ChaLearn Challenges in Machine Learning, leading ChaLearn Looking at People events. </p></td>
+  </tr>
+
+  <tr>
+    <td width="200px"><img src="images/XavierBaro.jpeg" alt="Xavier Baro" style="max-width:100%;"></td>
+    <td><p>Xavier Baró Solé is a professor in the Computer Science Department at the Universitat Autònoma de Barcelona (UAB), a Teacher Assistant at the Universitat de Barcelona (UB), and an Associate Professor at the Faculty of Computer Science, Multimedia and Telecommunication in the Universitat Oberta de Catalunya (UOC). His research interests are related to machine learning, evolutionary computation, and statistical pattern recognition.</p></td>
+  </tr>
+
+</table>
+
+### Administrators of the public instances
+
+<table>
+  <tr>
+    <td width="200px"><img src="https://user-images.githubusercontent.com/11784999/228867647-a4c26e61-68b4-4fc1-a643-24aa07a11d75.jpg" alt="" style="max-width:100%;"></td>
+    <td><p>Anne-Catherine Letournel is research engineer at the Laboratoire Interdisciplinaire des Sciences du Numérique (LISN), University Paris-Saclay. Her focus is leveraging the engineering software resources across all scientific teams of the lab: data science, interaction and visualization, HPC, algorithmics and combinatorics, bioinformatics. Her favorite domain has turned to be data science, mainly through CodaLab project since 2019.</p></td>
+  </tr>
+
+  <tr>
+    <td width="200px"><img src="https://user-images.githubusercontent.com/11784999/228864577-dbf74c6d-8d86-49df-a168-fb0d22dbe7b6.jpg" alt="" style="max-width:100%;"></td>
+    <td><p><a href="https://adrienpavao.com/">Adrien Pavão</a> is a research engineer working on improving CodaLab Competitions and Codabench platforms, and on organizing ambitious machine learning challenges such as <a href="https://autodl.chalearn.org/">AutoDL</a> and <a href="https://l2rpn.chalearn.org/">L2RPN</a>. He realized a PhD at Université Paris-Saclay, under the supervision of Isabelle Guyon. His research topics include the methodology and experimental design in machine learning, the performance comparison between models and the organization of competitions.</p></td>
+  </tr>
+
+  <tr>
+    <td width="200px"><img src="https://github.com/user-attachments/assets/2aacb2df-1755-4df1-b8ca-113be95d257c" alt="" style="max-width:100%;"></td>
+    <td><p>Obada Haddad-Soussac is a research engineer working on maintaining the infrastructure behind Codabench and Codalab. </p></td>
+  </tr>
+
+  <tr>
+    <td width="200px"><img src="https://github.com/codalab/codalab-competitions/assets/11784999/1fd28824-3011-453a-b99e-9eabf6c8852a" alt="" style="max-width:100%;"></td>
+    <td><p>Laurent Darré is research engineer at the Laboratoire Interdisciplinaire des Sciences du Numérique (LISN), University Paris-Saclay. He is the head of the laboratory's IT department. He joined the codalab project in 2016 to set up the first platforms at the Paris Saclay University.</p></td>
+  </tr>
+
+</table>
+
+
+### Acknowledgments
+
+CodaLab has received important contributions from many people, and we would like to thank their efforts in making CodaLab what it is today:
+
+Benjamin Aaron Bearce, Pujun Bhatnagar, Feng Bin, Justin Carden, Richard Caruana, Francis Cleary, Laurent Darré, Sergio Escalera, Xiawei Guo, Jennifer He, Ivan Judson, Arslan Kabeer, James Keith, Lori Ada Kilty, Shaunak Kishore, Stephen Koo, Anne-Catherine Letournel, Zhengying Liu, Zhenwu Liu, Adrien Pavao, Pragnya Maduskar, Simon Mercer, Arthur Pesah, Christophe Poulain, Lukasz Romaszko, Loïc Sarrazin, Laurent Senta, Xavier Baro Sole, Lisheng Sun, Tyler Thomas, Dinh Tuan Tran, Sebastien Treguer, Bailey Trefts, Nic Threfts, Wei-Wei Tu, Cedric Vachaudez, Paul Viola, Erick Watson, Zhen Xu, Tony Yang, Flavio Zhingri, Michael Zyskowski.
+
+[List of Github contributors](https://github.com/codalab/codalab-competitions/graphs/contributors)
+
+![](https://github.com/codalab/codalab-competitions/wiki/images/logo_collage.png)
diff --git a/documentation/GOVERNANCE.md b/documentation/GOVERNANCE.md
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+# CodaLab Community Governance
+
+
+CodaLab is an open-source, community-run project. A meritocracy model is used to govern the project’s needs, objectives and future goals.
+
+## Mission Statement
+The purpose of CodaLab is to provide an open-source platform to support and accelerate data and computationally-intensive research in a collaborative cloud-enabled environment.
+
+### Core Team 
+**Role:** The core team is responsible for strategic planning, maintaining account information for Codalab at https://github.com/codalab/codalab and approving changes to the governance model. It also makes decisions when community consensus cannot be reached.
+
+**How to join:** The core team is open to anyone who has invested a significant amount of time either as a Content Contributor (through uploading algorithms and datasets) or as a Framework Contributor of many patches. New members are accepted via majority vote by the existing members. Currently, the core team consists of developers, testers, and at least one representative from each of the current main university and industry partners.
+
+### Framework Contributors
+**Role:** A Framework Contributor is anyone who submits a patch to the project that adheres to the mission statement. At first, the patches should be small, but can grow once Committers express confidence in the quality of the Framework Contributor’s patches.
+For non-trivial patches (over 50 lines of code): Before a Framework Contributor’s first patch is put into the repository they must sign a Contributor License Agreement (CLA). We use the standard GitHub CLA, see https://cla.github.com/agreement.
+
+**How to join:** Submit a patch as a pull request to https://github.com/codalab/codalab. Patches must adhere to the conventions found at http://www.python.org/dev/peps/pep-0008/. All patches must be accompanied by unit tests before being accepted.
+
+### Committers
+**Role:** Committers decide on whether patches from Framework Contributors are entered into the main code repository. Committers use lazy consensus (see below) to decide on whether to commit a patch from a Framework Contributor. If the discussion does not move towards a consensus a decision will be made by a majority of (voting) core team members.
+
+**How to join:** You should be a Contributor (Framework or Content) and be nominated to the core team as a committer. Nominations should be sent to info@codalab.org. You may nominate yourself.
+
+### Content Contributors 
+**Role:** The main value of CodaLab comes from having the user-contributed content (the algorithms and datasets) on http://www.codalab.org, which can be edited in a Wikipedia style and used by anyone. The Content Contributors’ goal is to make the content organized and maximally useful.
+
+**How to join:** Contribute a handful of high-quality general modules or add documents/tutorials to http://www.codalab.org.
+
+## Communication
+Public discussions on any CodaLab topic should be held on the codalabdev@googlegroups.com discussion group.
+
+Non-public discussions on issues of governance, overall strategy and implementation issues are held at codalabcommitters@googlegroups.com. This discussion group is available to Committers only (see above). Note that this is not intended to be used frequently; by default all discussions should be open to everyone.
+
+## Decision-making
+Decisions are made default by lazy consensus: Someone (e.g., a committer) makes a proposal. If there are no objections within 72 hours, he or she can assume the community is in consensus and can move ahead with its implementation. If a consensus cannot be reached, then the core team votes.
+
+Decision-making is made in a transparent, open fashion. No decisions about the project’s direction, bug fixes or features may be done without community involvement and participation.