Projects

ML-Synthom – Fertigungsnahes Maschinelles Lernen für die Automobilzuliefererindustrie durch synthetische Generierung von Oberflächen und Materialien

Ensuring industrial quality through new research The ML-SYNTHOM project is developing an AI-based test procedure for quality assurance for new types of components in industrial production. The innovat

Data4Transparency – Data Science and NLP for transparency

According to the World Bank and the UN, some US$1tn is paid in bribes every year. Corrupt financial transactions divert funds from legitimate public services, as well as distort free markets—potential

KiBATIN – AI-based assistance system for triaging in the emergency room

In emergency rooms, speed is of the essence. According to the regulations on emergency care, emergency staff must assess within ten minutes how urgently patients need to be treated. Especially in phas

Adra-e – AI, Data and Robotics ecosystem

Adra-e - Supporting the AI, Data and Robotics Community in the Development of a Sustainable European Ecosystem Adra-e is a Coordination and Support Action (CSA) funded by the European Commission under

AIQUAMA – AI-based Quality Management for Smart Factories

Anomalies and defects in the production process cause high costs and have a negative impact on sustainability and productivity. If it is possible to detect such defects immediately when they occur, th

FLUENTLY – Fluently - the essence of human-robot interaction

Fluently leverages the latest advancements in AI-driven decision-making process to achieve true social collaboration between humans and machines while matching extremely dynamic manufacturing contexts

SEMSAI – Self-Referential Multi-Scale Modelling and Simulation of Severe Infectious Diseases

The Covid 19 pandemic has shown that model-based forecasts based on historical data often overestimate infection numbers, which weakens public acceptance of these forecasts as a basis for policy decis

PYSA – Care documentation with a hybrid speech assistant

Comprehensive and accurate documentation is essential for needs-based care. In many places, the systems and processes used today for care documentation are time-consuming and prone to errors. Caregive

SC_Gomaa – TeachTAM: Machine Teaching with Hybrid Neurosymbolic Reinforcement Learning; The Apprenticeship Model

Recent advances in Machine learning (specifically Computer Vision and Reinforcement Learning) allowed robots to understand objects and the surrounding environment on a perceptual non-symbolic level (e

SDE – Smart Dialogue Engine - AI model for controlling the dialog behavior of digital telephone assistants

The aim of the project is to research an AI model (Smart Dialogue Engine, SDE) that better adapts the dialogue behavior (course, choice of words, prosody) of telephone-based language assistants to the