Moritz von Zahn is a leading expert in applied data science at Tomorrow University, specializing in causal machine learning, explainable AI, and algorithmic fairness. With a strong academic foundation forged through collaborations with institutions like Goethe University Frankfurt, ETH Zurich, and the University of Tel Aviv, he merges innovative research with practical applications. Moritz’s extensive experience spans publishing in high-impact journals, reviewing for major conferences, and contributing to transformative projects with companies such as Swisscom AG, Payback GmbH, and McKinsey & Company. His work empowers learners and industry alike to harness the potential of AI responsibly and effectively.
Causal Machine Learning
Explainable AI
Algorithmic Fairness
Human-AI Collaboration
Ethical AI Deployment
Feature Selection Methods
Digital Footprint Analysis
Predictive Analytics
Transparent AI Design
Algorithm Development
Decision Support Systems
Green Nudges in AI
Data Science Fundamentals
Predictive Maintenance Strategies
Research Methodologies
Data Visualization
Peer-Review Processes
AI Ethics
E-Commerce Optimization
Academic Writing
The cost of fairness in AI: Evidence from e-commerce M von Zahn, S Feuerriegel, N Kuehl Business & Information Systems Engineering 64, 335–348, 2022
Expl(AI)ned: The impact of explainable artificial intelligence on users' information processing K Bauer, M von Zahn, O Hinz Information Systems Research, forthcoming, 2023
Designing a feature selection method based on explainable artificial intelligence J Zacharias, M von Zahn, J Chen, O Hinz Electronic Markets 32 (4), 2159-2184, 2022
Towards designing a user-centric decision support system for predictive maintenance in SMEs D Kellner, M Lowin, M von Zahn, J Chen INFORMATIK 2021
Locating disparities in machine learning M von Zahn, O Hinz, S Feuerriegel arXiv preprint arXiv:2208.06680, 2022
Please Take Over: XAI, Delegation of Authority, and Domain Knowledge K Bauer, M von Zahn, O Hinz SAFE Working Paper, 2023
The smart green nudge: Reducing product returns through enriched digital footprints & causal machine learning M von Zahn, K Bauer, C Mihale-Wilson, J Jagow, M Speicher, O Hinz SAFE Working Paper
Reviewing
Reviewer for Conferences:
International Conference of Information Systems (ICIS), European Conference of Information Systems (ECIS), Wirtschaftsinformatik (WI)
Reviewer for Journals:
Business & Information Systems Engineering (BISE)
Invited research talks at: University of Cologne, University of Zurich, LMU Munich, TU Clausthal, Karlsruhe Institute of Technology (KIT), University of Tel Aviv