community/working-groups/research/Topic4_AI-for-Scientific-Computing.md

# Topic4：AI for Scientific Computing

## Motivation：
* AI modeling：AI automatic modeling can effectively improve modeling efficiency of scientific calculations, and convergence analysis can improve model reliability and ensure simple and safe use by users.
* AI solution：The calculation amount of high-order differential increases exponentially with the parameter and the order. We can design neural network models to solve such classic problems.

## Target：
 * AI modeling：Construct a neural network, training data and loss function for scientific computing problems.
 * AI solution：AI model solves differential equations, solves optimization problems,  achieve the goal that the amount of high-order automatic differential calculation increases linearly with the order.

## Method：
​We expect the applicant can conduct  AI for scientific computing research based on MindSpore, and hope to get your valuable suggestions to MindSpore in the process. We will do our best to improve the capabilities of the MindSpore framework and  provide you with the most powerful technical support.

## How To Join：
* Submit an issue/PR based on community discussion for consultation or claim on related topics
* Submit your proposal to us by email <wang1@huawei.com>