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blog/2024-08-26-gsoc-2024-wraps-up.md

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3. Sambhav Dixit: "Machine Learning Downscaling of PEcAn Outputs" used Convolutional Neural Networks to enable downscaling of ecosystem model output to high spatial resolution while retaining information contained in ensemble based uncertainty estimates. His final report ["Linking Earth System Modeling and Machine Learning: My GSoC Journey with PEcAn"](https://medium.com/@indosambhav/revolutionizing-climate-modeling-my-gsoc-journey-with-pecan-3232f6b18da3) is on Medium.
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4. Meet Agrawal worked on "PEcAn Code Hardening by Integration Tests", a project that enhanced the reliability of PEcAn's codebase by improving integration tests.
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4. Meet Agrawal worked on "PEcAn Code Hardening by Integration Tests", a project that enhanced the reliability of PEcAn's codebase by improving integration tests. His final report ["GSoC 2024 : Final Report"](https://medium.com/@meetagrawal09/google-summer-of-code-2024-final-report-f7efd59466c6) is on Medium.
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These projects helped advance PEcAn's code, provided valuable experiences to both mentees and mentors. We are grateful to the participants, mentors, and everyone in the PEcAn community who continue to make the project and our GSOC experiences a success.
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