Google Summer of Code (GSoC)
Google Summer of Code (GSoC) is a global program focused on bringing new developers into open source software development. Since 2011, the INCF network has served as a mentoring organization that pairs GSoC candidates with developers from its community to work on 3-month programming projects. GSoC contributors are paid a stipend by Google. Between 2016 and 2020, when the program still was focused on students, INCF paired 87 students with 107 mentors.
GSoC 2023
Important links:
Google Summer of Code FAQ
Google Summer of Code 2023 timeline
Recommendations for GSoC contributors
Google Summer of Code guides for mentors and students
Read our blog about GSoC 2023
GSoC 2023 accepted projects
| Contributor | Mentor | Title |
| Aaryan Gautam | Dimiter Prodanov | 18.2 Image feature and classification database (350 h) |
| Abhijit Deo | Lia Domide, Romina Baila | 1.1 Integrate TVB with Zenodo (175/350 h) |
| Abhishek Tiwari | Marcel Stimberg, Dan Goodman, Ben Evans | 22.3 Code editor support for Brian model equations (175h/350h) |
| Aditya Agarwal | Satrajit Ghosh, Dorota Jarecka, Ghislain Vaillant | 16.1 Adding new workers and resource management to new dataflow engine written in Python: Pydra (175 h) |
| Arya A | Malvika Sharan, Johanna Bayer | 19.1 The Turing Way: A how-to guide to data science (175/350 h) |
| Carolina Fernandez | Nicholas Tolley, Stephanie Jones, Mainak Jas, Ryan Thorpe | 2.2 Generalize parameter optimization routines (350 h) |
| Daksh Rathore | Ankur Sinha, Padraig Gleeson, Björn Brembs | 21.2 Open Source Brain 2: Conversion of public neurophysiology datasets to Neurodata Without Borders (NWB) format (175h/350h) |
| Dishie | Daniele Marinazzo, Etienne Combrisson | 5.1 Optimization of the computations of higher-order interactions and integration in the Frites python package (175 h) |
| Himanshu Chougule | Jesse Parent, Bradly Alicea, Jiahang Li, Mayukh Deb | 3.1 D-GNNs: developing DevoGraph for computational developmental biology (OpenWorm Foundation) (350 h) |
| Irene Bernardi | Valery Bragin, James Chen | 9.1 Multiscale brain circuit modeling using NetPyNE: model conversion and machine learning analysis (175/350 h) |
| Jyothi Swaroop Reddy Bommareddy | Suresh Krishna, JB Poline, Yohaï-Eliel Berreby, Floris van Vugt, Vincent Larivière, Björn Brembs | 13.1 A social-web tool to facilitate rating and commenting on research reports (350 h) |
| Kshitiz Sareen | Anca Doloc-Mihu, Cengiz Gunay | 7.1 Working on implementing CSV data browser and querying component (350 h) |
| Pon Raja Prabhu | Anca Doloc-Mihu, Cengiz Gunay | 7.2 Working on improving graphical interface and user experience (175 h) |
| R. V. Prajagopalan | Jesse Parent, Bradly Alicea | 4.1 Maintaining an Open-source Sustainability Project (Orthogonal Research and Education Lab) (350 h) |
| Rajat Partani | Nicholas Tolley, Stephanie Jones, Mainak Jas, Ryan Thorpe | 2.1 Develop IO routines for HNN-core outputs (350 h) |
| Sanjay Thiyagarajan | Christine Rogers, racostas, Laetitia Fesselier | 17.1 Contribute to LORIS (175/350 h) |
| Soham Mulye | Suresh Krishna, Arvind Chandna, Yohaï-Eliel Berreby, Floris van Vugt | 8.1 Efficient app-based measurement of visual functions in in infants and young children (350 h) |
| Subhankar Panda | Titipat Achakulvisut, Daniele Marinazzo, Björn Brembs | 11.1 Improving automatic reviewer assignment using large language models for NBDT journal (350 h) |
| Sumit Pagar | Lia Domide, Romina Baila | 1.2 Structural Connectivity editor widget (175/350 h) |
| Sushmanth Reddy Mereddy | Jesse Parent, Bradly Alicia, Jiahang Li, Mayukh Deb | 3.1 D-GNNs: developing DevoGraph for computational developmental biology (OpenWorm Foundation) (350 h) |
| Vrushali Nandurkar | Jesse Parent, Bradly Alicia | 4.2 Virtual Reality for Distributed Research (Orthogonal Research and Education Lab) (175 h) |
| Atharva Purohit | Arnab Banerjee | 20.1 Impact visualization portal for global neuro-informatics community (175 h) |
| Eslam Khaled Korany | Szabolcs Kali, Sára Sáray, Martin Blazsek, Máté Mohácsi | 15.1 Integration of automated model testing and parameter fitting tools for neuroscience applications (175/350 h) |
