AI-based Decision Support

Within this field, we develop state-of-the-art predictive and prescriptive AI-based systems that support processes and decisions utilizing multimodal data (e.g., images, videos, text, tabular sensor data). Oftentimes, the challenge lies in balancing model building and data engineering to design systems that provide accurate information for decision-makers or automated decision systems.

Example Projects:

AI-based Optimizing of End-of-Life Solar Panel Recycling
Designing AI-based System for Strategic Decision-Making
Image-based Trading Agents via Explainable Reinforcement Learning Learning
Explainable Reinforcement Learning for Solving the Dynamic Ambulance Relocation and Dispatching Problem

Publications:

Graf, J., Lancho, G., Heinrich, K., Möller, F., Schoormann, T., & Zschech, P. (2025). Designing a Neural Question-Answering System for Times of (Information) Pandemics. Information Systems Management, 1-21. https://doi.org/10.1080/10580530.2025.2507175
Heinrich, K., & Keshavarzi, A. (2024). Are Our Predictions Healthy? A Comparative Meta-Analysis of Machine Learning Studies in Predictive Healthcare. ECIS 2024 Proceedings.
Janiesh, C., Zschech, P., & Heinrich, K. (2021). Machine learning and deep learning. Electron Markets, 31, 685-695. https://doi.org/10.1007/s12525-021-00475-2