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Pre- and Postdocs
In addition to the more than 20 professorships related to AI, BaCAI includes many doctoral students and postdoctoral researchers. Here you will find researchers who are conducting research in various areas of artificial intelligence at or in close collaboration with the University of Bamberg.
Chair of Cognitive Systems /
Sony AI Labs Barcelona
Neuro-symbolic learning and reasoning
Chair for AI Engineering in Companies
Social impact assessment of the use of generative AI in relation to misinformation
An XAI Framework for Human-Guided Explanation in Complex Knowledge Domains
Chair for AI Systems Engineering
Universal Logic in and for AI
Chair for AI Systems Engineering
Trustworthy Citizen Participation in Smart Cities
Explainable Artificial Intelligence on Time Series Data
Chair of Information Systems, esp. AI Engineering in Companies
Reduction of people's rejection of technologies, especially AI-based systems
Chair of Information Systems, esp. AI Engineering in Companies
Using AI to detect hate messages and combat fake news
Chair of Cognitive Systems / Continental
xAI for Safety: Understanding and adapting deep learning models for computer vision tasks
Chair for Information Visualization
Comparative and Collaborative Visual Analysis of Clustering and Co-clustering Ensembles
Relational Explanations for Visual Domains: A Neural-symbolic Approach Combining ILP and CNNs
Chair for explainable Artificial Intelligence
Towards Robust Neural Networks for Affect Recognition: Leveraging Domain Knowledge in Data Preprocessing, Model Training, and Evaluation
Chair of Information Systems, esp. AI Engineering in Companies
Polarization on social media, esp. using social media analytics and AI to investigate social phenomena
Chair of Cognitive Systems / BMW
Comprehensible time series forecasting using Knowledge Graphs: From Market Research and Event Data Modeling to Explainable Clustering and Forecasting
Enhancing Explanatory Interactive Machine Learning – A Generalization of the CAIPI Algorithm
Chair for AI Systems Engineering
Automated Content Moderation using Hybrid AI Systems
Utilizing Interactive Multi Modal Machine Learning for Forest Inventory and Tree Vitality Assessment
Christoph Wehner
Lehrstuhl für Kognitive Systeme
Interactive and Explainable Machine Learning on Knowledge Graphs