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Research Group Christoph Kern


Link to website at LMU

Christoph Kern

Prof. Dr.

Associate

Christoph Kern

is Junior Professor of Social Data Science and Statistical Learning at LMU Munich.

His work focuses on the reliable use of machine learning methods and new data sources in social science, survey research, and algorithmic fairness.

Team members @MCML

PhD Students

Link to website

Unai Fischer Abaigar

Link to website

Leonhard Kestel

Link to website

Marcus Novotny

Link to website

Jan Simson

Recent News @MCML

Link to Rethinking AI in Public Institutions - Balancing Prediction and Capacity

09.10.2025

Rethinking AI in Public Institutions - Balancing Prediction and Capacity

Link to Outstanding Paper Award at ICML 2025 for MCML Researchers

18.07.2025

Outstanding Paper Award at ICML 2025 for MCML Researchers

Link to MCML at ICML 2025: 25 Accepted Papers (20 Main, and 5 Workshops)

10.07.2025

MCML at ICML 2025: 25 Accepted Papers (20 Main, and 5 Workshops)

Link to Why Causal Reasoning Is Crucial for Reliable AI Decisions

12.06.2025

Why Causal Reasoning Is Crucial for Reliable AI Decisions

Link to MCML at CHI 2025: Seven Accepted Papers

25.04.2025

MCML at CHI 2025: Seven Accepted Papers

Publications @MCML

2025


[30]
S. Eckman • B. MaC. Kern • R. Chew • B. PlankF. Kreuter
Aligning NLP Models with Target Population Perspectives using PAIR: Population-Aligned Instance Replication.
NLPerspectives @EMNLP 2025 - 4th Workshop on Perspectivist Approaches to NLP at the Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. To be published. Preprint available. arXiv

[29]
J. Kappenberger • C. Strasser Ceballos • F. Gerdon • D. Szafran • F. Rupp • K. Eckert • H. Stuckenschmidt • R. Bach • F. KreuterC. Kern
Unintended Impacts of Automation for Integration? Simulating Integration Outcomes of Algorithm-Based Refugee Allocation in Germany.
AIES 2025 - AAAI/ACM Conference on AI, Ethics, and Society. Madrid, Spain, Oct 20-25, 2025. DOI

[28]
C. Strasser Ceballos • M. NovotnyC. Kern
Beyond Proxy Variables: Extending Refugee Allocation Algorithms for Equitable Predictions.
AIES 2025 - AAAI/ACM Conference on AI, Ethics, and Society. Madrid, Spain, Oct 20-25, 2025. DOI

[27]
J. Beck • S. Eckman • C. KernF. Kreuter
Bias in the Loop: How Humans Evaluate AI-Generated Suggestions.
Preprint (Sep. 2025). arXiv

[26]
J. Collins • C. Kern
Pre-Trained Nonresponse Prediction in Panel Surveys with Machine Learning.
Survey Research Methods 19.2. Aug. 2025. DOI

[25]

[24] A* Conference
U. Fischer AbaigarC. Kern • J. Perdomo
The Value of Prediction in Identifying the Worst-Off.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. Spotlight Presentation. Outstanding Paper Award. To be published. Preprint available. arXiv

[23]

[22]
U. Fischer AbaigarC. KernF. Kreuter
Adjusting survey estimates with multi-accuracy post-processing.
ITACOSM 2025 - Italian Conference on Survey Methodology. Bologna, Italy, Jul 01-04, 2025. Invited talk. To be published. Preprint available.

[21]
P. O. SchenkC. Kern • T. D. Buskirk
Fares on Fairness: Using a Total Error Framework to Examine the Role of Measurement and Representation in Training Data on Model Fairness and Bias.
EWAF 2025 - 4th European Workshop on Algorithmic Fairness. Eindhoven, The Netherlands, Jun 30-Jul 02, 2025. URL

[20]
C. Strasser Ceballos • M. NovotnyC. Kern
Re-evaluating the role of refugee integration factors for building more equitable allocation algorithms.
EWAF 2025 - 4th European Workshop on Algorithmic Fairness. Eindhoven, The Netherlands, Jun 30-Jul 02, 2025. URL

[19]
C. Strasser Ceballos • C. Kern
Location matching on shaky grounds: Re-evaluating algorithms for refugee allocation.
ACM FAccT 2025 - 8th ACM Conference on Fairness, Accountability, and Transparency. Athens, Greece, Jun 23-26, 2025. DOI

[18]
C. Kern • U. Fischer-Abaigar • J. SchweisthalD. Frauen • R. Ghani • S. Feuerriegel • M. van der Schaar • F. Kreuter
Algorithms for reliable decision-making need causal reasoning.
Nature Computational Science 5. May. 2025. DOI

[17]
R. L. Bach • C. Kern
Fairness, Justice, and Social Inequality in Machine Learning.
Preprint (May. 2025). DOI

[16] A* Conference
J. Simson • F. Draxler • S. Mehr • C. Kern
Preventing Harmful Data Practices by Using Participatory Input to Navigate the Machine Learning Multiverse.
CHI 2025 - Conference on Human Factors in Computing Systems. Yokohama, Japan, Apr 26-May 01, 2025. DOI

[15] A* Conference
C. Kern • M. P. Kim • A. Zhou
Multi-Accurate CATE is Robust to Unknown Covariate Shifts.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. Journal Track. URL URL

[14]
E. Achterhold • M. Mühlböck • N. Steiber • C. Kern
Fairness in Algorithmic Profiling: The AMAS Case.
Minds and Machines 35.9. Jan. 2025. DOI

2024


[13]
U. Fischer AbaigarC. Kern • N. Barda • F. Kreuter
Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector.
Government Information Quarterly 41.4. Dec. 2024. DOI

[12]
C. Kern • R. Bach • H. Mautner • F. Kreuter
When Small Decisions Have Big Impact: Fairness Implications of Algorithmic Profiling Schemes.
ACM Journal on Responsible Computing. Nov. 2024. DOI

[11]
P. O. SchenkC. Kern
Connecting algorithmic fairness to quality dimensions in machine learning in official statistics and survey production.
AStA Wirtschafts- und Sozialstatistisches Archiv 18. Oct. 2024. DOI

[10]
C. Kern • M. P. Kim • A. Zhou
Multi-Accurate CATE is Robust to Unknown Covariate Shifts.
Transactions on Machine Learning Research. Oct. 2024. Certifications: Featured. URL

[9]
U. Fischer AbaigarC. KernF. Kreuter
The Missing Link: Allocation Performance in Causal Machine Learning.
Workshop Humans, Algorithmic Decision-Making and Society @ICML 2024 - Workshop Humans, Algorithmic Decision-Making and Society: Modeling Interactions and Impact at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. arXiv URL

[8]
E. Kraus • C. Kern
Measurement Modeling of Predictors and Outcomes in Algorithmic Fairness.
EWAF 2024 - 3rd European Workshop on Algorithmic Fairness. Mainz, Germany, Jul 01-03, 2024. PDF

[7]
J. Simson • A. Fabris • C. Kern
Unveiling the Blindspots: Examining Availability and Usage of Protected Attributes in Fairness Datasets.
EWAF 2024 - 3rd European Workshop on Algorithmic Fairness. Mainz, Germany, Jul 01-03, 2024. PDF

[6]
C. Strasser Ceballos • C. Kern
Deciding the Future of Refugees: Rolling the Dice or Algorithmic Location Assignment?
EWAF 2024 - 3rd European Workshop on Algorithmic Fairness. Mainz, Germany, Jul 01-03, 2024. PDF

[5]
S. Jaime • C. Kern
Ethnic Classifications in Algorithmic Fairness: Concepts, Measures and Implications in Practice.
ACM FAccT 2024 - 7th ACM Conference on Fairness, Accountability, and Transparency. Rio de Janeiro, Brazil, Jun 03-06, 2024. DOI

[4]
J. Simson • A. Fabris • C. Kern
Lazy Data Practices Harm Fairness Research.
ACM FAccT 2024 - 7th ACM Conference on Fairness, Accountability, and Transparency. Rio de Janeiro, Brazil, Jun 03-06, 2024. DOI

[3]
J. Simson • F. Pfisterer • C. Kern
One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design Decisions.
ACM FAccT 2024 - 7th ACM Conference on Fairness, Accountability, and Transparency. Rio de Janeiro, Brazil, Jun 03-06, 2024. DOI

[2]