Projects from Prof. Dr. Axel-Cyrille Ngonga Ngomo
SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems
Current systems that incorporate AI technology mainly target the introduction phase, where a core component is training and adaptation of AI models based on given example data. SAIL’s focus on the full life-cycle moves the current emphasis towards sustainable long-term development in real life. The joint project SAIL addresses both basic research ...
Duration: 08/2022 - 07/2026
NEBULA: Nutzerzentrierte KI-basierte Erkennung von Fake-News und Fehlinformationen
The goal of this interdisciplinary project is the transparent, AI-based detection of Fake News and false information in security-relevant situations and a presentation of the detection results that is suitable for the target audience and boosts the audiences media literacy.Funding programThis work is supported by the German Federal Ministry of ...
Duration: 07/2022 - 12/2025
Colide: Co-Training and Co-Regulierung für Industriedaten
Ziel von COLIDE ist die Entwicklung von Auto-Multi-View-Learning-Verfahren (AutoMVL) für heterogene Industriedaten. Dazu werden multi-view learning (MVL) und automatisiertes maschinelles Lernen (AutoML) erstmals kombiniert. Damit werden insbesondere KMUs in die Lage versetzt, den Mehrwert der simultanen Nutzung verschiedenster ML-Methoden auf ...
Duration: 05/2021 - 04/2024
SPEAKER: A language assistance platform "Made in Germany"
Voice assistants are a core technology for human-machine interaction and provide access to product offerings and services via natural language. So far, companies in the US and Asia have dominated the market for voice assistance technology. However, the demand for voice assistant solutions in German production and retail industries is enormous, ...
Duration: 04/2020 - 03/2023
EML4U: Erklärbares Maschinelles Lernen für interaktive episodische Updates von Modellen
The goal of the project is to develop methods of ML explainability for a question that is highly relevant for practice: Which explanations can be offered to the user to make episodic interactive learning efficient and valid, especially in applications where manual data annotation is costly? In addition to a classical feature representation of data, ...
Duration: 04/2020 - 03/2022
DAIKIRI: Diagnostische KI für industrielle Daten
Das Forschungsprojekt DAIKIRI zielt auf die erstmalige Entwicklung und Verwendung von automatischen Verfahren für die Semantifizierung von industriellen Daten und die datengetriebene Diagnose von Industrieanlagen ab. Mit Hilfe dieser Verfahren sollen diagnostische selbsterklärende Smart-Services für Industriedaten entwickelt und mit Daten aus ...
Duration: 01/2020 - 06/2022