Machine Learning for High-Throughput Methods and Mechatronics (ML4HOME)

The research group “Machine Learning for High-Throughput Methods and Mechatronics” (ML4HOME) deals with the analysis of data being generated automatically by mechatronic systems in big amounts. We aim for models based on labeled / unlabeled images or time-series. Our focus is the generalization of big data-sets consisting of a lot of data points (high-throughput), whose extent requires mandatory automatic processing.

To ensure the usability of all developed algorithms and derived knowledge, we integrate our software typically into the open source MATLAB toolbox SciXMiner.

 

Program:

BioInterfaces in Technology and Medicine (BIFTM)

 

Projects:

              

Completed Projects:

 

Team

Head of Group: apl. Prof. Dr. Markus Reischl
Name Phone E-mail
Moritz Böhland +49 721 608-25755
+49 721 608-43531		 moritz boehlandEzc0∂kit edu
Lisa Petani, M.Sc. +49 721 608-25761 lisa petaniGeq2∂kit edu
apl. Prof. Dr. Christian Pylatiuk   pylatiukVgj7∂kit edu
apl. Prof. Dr. Markus Reischl +49 721 608-25749 markus reischlYkj4∂kit edu
Marcel Schilling, M.Sc. +49 721 608-25739 marcel schillingNxz7∂kit edu
Jan Schützke, M.Sc.    
Yanke Wang   yanke wangLlw4∂kit edu
2 additional persons visible within KIT only.
Employees in training (DHBW)
Name Phone E-mail
1 additional person visible within KIT only.
Employees in training
Name Phone E-mail
1 additional person visible within KIT only.