Topic

This lab is about developing of machine learning software tool for building applications. The diversity of solutions by choosing different routines (ANN/Seq2Seq/. . . ) and preprocessing ideas and the effect on the hardware performance, is the key to develop general software where the user can choose between different self-programmed idea and architecture of Machine Learning and read the necessary outcome from it (Can include benchmarking test and mathematical outcome).

Tasks

In the beginning of the course, the groups will have small introduction to the state of the art and application of machine learning on buildings, than each group will make a brainstorm to decide the technical solutions and ideas to implement after doing a presentation research (each presentation will be discuss it individually). In the end each group will present the implemented tools and solutions for all participants.

”The winning strategy with the best accuracy, innovation and creation of solutions and potential of testing will define the 2021 winning group!”

Requirements

Knowledge in machine learning programming (Python,Matlab,C sharp,C++) and parallel computing is recommended, knowing about Agile and scrum techniques and software management tools is an advantage.

There are weekly meetings where we can discuss the work progress, plan and ideas. All groups will present for 30mn about a topic chosen from a given list. We are looking for 4 groups of 2. If you are interested, please state your experience!

This lab will take place from begin of April until mid of July

Contact

This project takes place in the Theory of Hybrid Systems (i2) research group headed by Prof. Dr. Erika Ábrahám. The project will be co-supervised by Ahmed Abida . For further questions please contact Ahmed Abida.