Skip to main content

Intelligent systems are characterized by learning processes that allow the acquisition of new skills and deal with a large amount of heterogeneous, uncertain and probabilistic data. Due to the complexity of the real-world situations represented by them, the automatic abstraction of information from data, the formation of appropriate representative models, and the semantic processing of existing information is essential to build intelligent systems for digital transformation, such as mobility To enable industry, medicine and education.

Projekte

Alexandria

The ALEXANDRIA project (ERC Nr. 339233) aims to develop models, tools and techniques necessary to explore and analyze Web archives in a meaningful way

AMA - Applied Machine Learning Academy

The aim of the AMA project is s to build up the Applied Machine Learning Academy (AMA) based on a sustainable, flexible and applied qualification concept

AutoPIN

Machine learning and signal processing for automatic analysis of sensor data

BacData

Building an analytics framework for precision microbiology to fight biofilm-associated infections

BIAS

Bias and Discrimination in Big Data and Algorithmic Processing. Philosophical Assessments, Legal Dimensions, and Technical Solutions

Big Data for Cochlea Implants

Understanding Cochlear Implant Outcome Variability using Big Data and Machine Learning Approaches

BigMedilytics

 Application of Big data technologies for supporting more efficient and effective healthcare systems

BLINKER

The BLINKER project is a collaboration between L3S and Goetting KG, a company which is specialized on driverless transportation systems

BOOST4.0 - Big Data for Factories

Big Data Value Spaces for COmpetitiveness of European COnnected Smart FacTories 4.0

BRENDA II

BRaunschweig ENzyme DAtabase ist das weltweit größte Informationssystem für biochemische, molekularbiologische und funktionale Enzymdaten