Add SPINN project

Author: ereinha

_gsocprojects/2026/project_SPINN.md

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+---
+project: SPINN
+layout: default
+logo: SPINN_image_cropped.png
+description: Shape optimization is an essential task in many engineering and physics domains when the geometry of an object strongly influences its performance and efficiency. The Shape optimization via Physics-Influenced Neural Networks (SPINN) project aims to automate and streamline the task of shape optimization via the use of Physics Influenced Neural Networks and Coordinate Projection Networks.
+---
+
+{% include gsoc_project.ext %}

_gsocproposals/2026/proposal_SPINN1.md

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+---
+title: Semi-supervised Symmetry Discovery
+layout: gsoc_proposal
+project: SPINN
+year: 2026
+organization:
+  - Alabama
+  - Cerium
+
+---
+
+## Description
+In many engineering and physics domains, the shape or geometry of an object directly influences its performance with regard to some metric. Simple examples include the shape of an airplane wing affecting its lift-to-drag ratio, or the geometry/structure of a bridge influencing the maximum load weight which can safely traverse it. “Shape optimization” refers to the task of identifying the ideal shape/geometry of such an object which can maximize or minimize a metric of interest with respect to that object. This project looks to leverage Physics Influenced Neural Networks (PINN) and Coordinate Projection Networks (also called shape networks in the literature) to develop machine learning architectures which can quickly and efficiently perform this task.
+
+## Duration
+Total project length: 175 hours.
+
+## Task ideas
+  * Identify relevant use-case scenario and develop a PINN to accurately model underlying physics.
+  * Perform model optimization of both PINN and coordinate projection network.
+
+## Expected results:
+  * PINN model with demonstrated ability to perform shape optimization.
+
+## Difficulty level
+Advanced
+
+## Requirements
+  * Essential: Experience in Python, PyTorch (or related ML framework), and machine learning are required. 
+  * Preferred: Familiarity with basic physics concepts (classical mechanics, electromagnetics, etc.) at an undergraduate level. 
+  * Will help you stand out: Experience performing physics simulations using standard simulation software (COMSOL, ANSYS, etc.) or an equivalent open source framework, and familiarity with associated concepts (numerical methods techniques, how to handle boundary conditions, etc.).
+
+<!---
+## Test
+Please use [this link](https://docs.google.com/document/d/10tITU-OJDtaZkLmXpoCpzIM55XcV4Z_7ykS7N9tyISA/edit?usp=sharing) to access the test for this project.
+--->
+
+## Mentors
+  * [Dale Julson](mailto:[email protected]) (Cerium Labs)
+  * [Eric Reinhardt](mailto:[email protected]) (University of Alabama)
+  * [Dinesh Ramakrishnan](mailto:[email protected]) (University of Alabama)
+
+Please **DO NOT** contact mentors directly by email. Instead, please email [[email protected]](mailto:[email protected]) with Project Title and **include your CV** and **test results**. The mentors will then get in touch with you.
+
+## Links
+  * [Paper 1](https://www.nature.com/articles/s41598-024-57137-4)
+  * [Paper 2](https://arxiv.org/abs/2201.05624)