Research areas

Research areas and expertise

The RCAI researches diverse facets of artificial intelligence.
When developing and implementing AI concepts, the RCAI follows a holistic approach and combines various AI technologies with the domain knowledge of its laboratories as well as with ethical, social and legal considerations.

Computer Vision

Image Reconstruction

Reconstruction of incomplete image data

Image Segmentation

Segmentation of a wide range of image data

Edge AI

Miniaturisation and integration of machine learning methods for image evaluation in sensor nodes

Object Detection

Detection and identification of objects in various scenarios

Computational Linguistics

Acoustic Speech Recognition

Electroacoustics and machine learning for understanding spoken language

Multimodal (Dialogue) Systems

Spoken language dialogue systems and multimodal language processing

Sentiment Analysis

Evaluation of text and language in terms of the emotions they express

Signal & time series analysis

Predictive Maintenance

Early detection of faults and defects based on signals from the production environment

Smart X

Analysing smart meter and sensor data for any use case

Simulation and prediction

Digital Models of the Human Body

Models and simulations for analysing the course of illness, surgery and rehabilitation

Intrusion Detection

Detection of cyber attacks, e.g. through anomaly detection

Prediction of Production Results

Feasibility assessment of additively manufactured components

Scenario Methods

Forecasting complex scenarios, e.g. for crisis management

Behavioural Analyses in the Energy Sector

Analysis of usage behaviour, prediction of loads and active and reactive power

Planning and control

Industrial Optimisation

Planning and optimisation of production processes and factory layouts with reinforcement learning

Planning and Optimisation for Infrastructure and Buildings

Optimised, intelligent electricity management and building planning

AI for Games

Reinforcement learning agents for computer games


Data Augmentation

Methods for the synthetic expansion of datasets using generative neural networks

Generation of New Structures

Generation of geometry data for CAD models

Detection of AI-Generated Content

AI to recognise artificially generated content, e.g. in social media

Cross-cutting aspects

Mathematical Foundations

Mathematical Foundations of Neural Networks

Physics-Informed AI

Combination of artificial intelligence and known physical models

Quantum AI

Quantum machine learning and optimisation algorithms for quantum computers

Software Engineering

Increasing and safeguarding software and system quality of and through AI

Economic aspects

Promotion of Start-ups

Spin-offs and start-ups in the field of artificial intelligence

IT Management

Management of information technologies such as cloud computing in corporate use

Human Resources and Accounting

Possible applications of AI, taking into account special regulatory requirements

Knowledge Transfer

Best practices for knowledge transfer in industry and society

Ethical, Legal and Social Aspects

Empirical Social Research

Investigation of social aspects of artificial intelligence using empirical social research methods

Technology Impact

Impact of artificial intelligence on society, mobility, energy, health, information and communication technology

Applied Ethics

Ethical aspects and framework conditions for the use of artificial intelligence