Research Group Christoph Kern
Christoph Kern
Prof. Dr.
Core PI
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
Unai Fischer Abaigar
→ Group Christoph Kern
Social Data Science and AI
→ Co-Group Frauke Kreuter
Leonhard Kestel
→ Group Christoph Kern
Social Data Science and AI
→ Co-Group Frauke Kreuter
Marcus Novotny
→ Group Christoph Kern
Social Data Science and AI
→ Co-Group Frauke Kreuter
Jan Simson
→ Group Christoph Kern
Social Data Science and AI
→ Co-Group Frauke Kreuter
Recent News @MCML
Publications @MCML
2026
[39]
L. B. Andersen • M. Herklotz • A. Liu • M. Goeke • M. Juelich • C. Kern • F. Kreuter
From Awareness to Action? The Impact of CO2 Emission Feedback on Student LLM Usage.
CHI 2026 - ACM CHI Conference on Human Factors in Computing Systems. Barcelona, Spain, Apr 13-17, 2026. DOI
From Awareness to Action? The Impact of CO2 Emission Feedback on Student LLM Usage.
CHI 2026 - ACM CHI Conference on Human Factors in Computing Systems. Barcelona, Spain, Apr 13-17, 2026. DOI
[38]
J. Beck • S. Eckman • C. Kern • F. Kreuter
Bias in the Loop: How Humans Evaluate AI-Generated Suggestions.
Harvard Data Science Review 8.2. Apr. 2026. DOI
Bias in the Loop: How Humans Evaluate AI-Generated Suggestions.
Harvard Data Science Review 8.2. Apr. 2026. DOI
[37]
R. Chew • S. Eckman • C. Kern • F. Kreuter
From Ground Truth to Measurement: A Statistical Framework for Human Labeling.
Preprint (Apr. 2026). arXiv
From Ground Truth to Measurement: A Statistical Framework for Human Labeling.
Preprint (Apr. 2026). arXiv
[36]
S. Dudy • J. Simson • Y. Long
'Taking Stock at FAccT': Using Participatory Design to Co-Create a Vision for the Fairness, Accountability and Transparency Community.
Preprint (Apr. 2026). arXiv
'Taking Stock at FAccT': Using Participatory Design to Co-Create a Vision for the Fairness, Accountability and Transparency Community.
Preprint (Apr. 2026). arXiv
[35]
X. Heilmann • C. Manganini • M. Cerrato • L. Kestel • V. Belle
A Neurosymbolic Approach to Counterfactual Fairness.
Neurosymbolic Artificial Intelligence 2. Mar. 2026. DOI
A Neurosymbolic Approach to Counterfactual Fairness.
Neurosymbolic Artificial Intelligence 2. Mar. 2026. DOI
[34]
I. D. Jimenez • C. Kern
Dialect and Gender Bias in YouTube's Spanish Captioning System.
Preprint (Feb. 2026). arXiv
Dialect and Gender Bias in YouTube's Spanish Captioning System.
Preprint (Feb. 2026). arXiv
[33]
J. Rodemann • U. Fischer Abaigar • J. Bailie • K. Muandet
Performative Learning Theory.
Preprint (Feb. 2026). arXiv
Performative Learning Theory.
Preprint (Feb. 2026). arXiv
[32]
J. Simson
Re-evaluating the machine learning pipeline to improve fairness and reliability.
Dissertation LMU München. Jan. 2026. DOI
Re-evaluating the machine learning pipeline to improve fairness and reliability.
Dissertation LMU München. Jan. 2026. DOI
2025
[31]
P. O. Schenk • C. Kern • F. Kreuter
Fairness in Machine Learning for National Statistical Organizations.
Foundations and Advances of Machine Learning in Official Statistics. Dec. 2025. DOI
Fairness in Machine Learning for National Statistical Organizations.
Foundations and Advances of Machine Learning in Official Statistics. Dec. 2025. DOI
[30]
S. Eckman • B. Ma • C. Kern • R. Chew • B. Plank • F. 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. DOI
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. DOI
[29]
J. Kappenberger • C. Strasser Ceballos • F. Gerdon • D. Szafran • F. Rupp • K. Eckert • H. Stuckenschmidt • R. Bach • F. Kreuter • C. 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
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. Novotny • C. 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
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]
Á. F. Junquera • C. Kern
From rules to forests: rule-based versus statistical models for jobseeker profiling.
Journal for Labour Market Research 59.26. Oct. 2025. Preprint. DOI
From rules to forests: rule-based versus statistical models for jobseeker profiling.
Journal for Labour Market Research 59.26. Oct. 2025. Preprint. DOI
[26]
J. Simson • A. Fabris • C. Fröhner • F. Kreuter • C. Kern
Bias Begins with Data: The FairGround Corpus for Robust and Reproducible Research on Algorithmic Fairness.
Preprint (Oct. 2025). arXiv
Bias Begins with Data: The FairGround Corpus for Robust and Reproducible Research on Algorithmic Fairness.
Preprint (Oct. 2025). arXiv
[25]
J. Collins • C. Kern
Pre-Trained Nonresponse Prediction in Panel Surveys with Machine Learning.
Survey Research Methods 19.2. Aug. 2025. DOI
Pre-Trained Nonresponse Prediction in Panel Surveys with Machine Learning.
Survey Research Methods 19.2. Aug. 2025. DOI
[24]
[23]
U. Fischer Abaigar • C. 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. URL
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. URL
[22]
M. Novotny • W. Weber • C. Kern • F. Kreuter
Measuring public opinion towards artificial intelligence: development and validation of a general AI attitude short scale.
AI and Society. Jul. 2025. DOI
Measuring public opinion towards artificial intelligence: development and validation of a general AI attitude short scale.
AI and Society. Jul. 2025. DOI
[21]
U. Fischer Abaigar • C. Kern • F. Kreuter
Adjusting survey estimates with multi-accuracy post-processing.
Invited Talk @ITACOSM 2025 - Italian Conference on Survey Methodology. Bologna, Italy, Jul 01-04, 2025. Invited Talk. PDF
Adjusting survey estimates with multi-accuracy post-processing.
Invited Talk @ITACOSM 2025 - Italian Conference on Survey Methodology. Bologna, Italy, Jul 01-04, 2025. Invited Talk. PDF
[20]
P. O. Schenk • C. 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
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
[19]
C. Strasser Ceballos • M. Novotny • C. 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
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
[18]
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
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
[17]
C. Kern • U. Fischer-Abaigar • J. Schweisthal • D. 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
Algorithms for reliable decision-making need causal reasoning.
Nature Computational Science 5. May. 2025. DOI
[16]
R. L. Bach • C. Kern
Fairness, Justice, and Social Inequality in Machine Learning.
Preprint (May. 2025). DOI
Fairness, Justice, and Social Inequality in Machine Learning.
Preprint (May. 2025). DOI
[15]
J. Simson • F. Draxler • S. Mehr • C. Kern
Preventing Harmful Data Practices by Using Participatory Input to Navigate the Machine Learning Multiverse.
CHI 2025 - ACM CHI Conference on Human Factors in Computing Systems. Yokohama, Japan, Apr 26-May 01, 2025. DOI
Preventing Harmful Data Practices by Using Participatory Input to Navigate the Machine Learning Multiverse.
CHI 2025 - ACM CHI Conference on Human Factors in Computing Systems. Yokohama, Japan, Apr 26-May 01, 2025. DOI
[14]
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
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
[13]
E. Achterhold • M. Mühlböck • N. Steiber • C. Kern
Fairness in Algorithmic Profiling: The AMAS Case.
Minds and Machines 35.9. Jan. 2025. DOI
Fairness in Algorithmic Profiling: The AMAS Case.
Minds and Machines 35.9. Jan. 2025. DOI
2024
[12]
U. Fischer Abaigar • C. 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
Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector.
Government Information Quarterly 41.4. Dec. 2024. DOI
[11]
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
When Small Decisions Have Big Impact: Fairness Implications of Algorithmic Profiling Schemes.
ACM Journal on Responsible Computing. Nov. 2024. DOI
[10]
P. O. Schenk • C. 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
Connecting algorithmic fairness to quality dimensions in machine learning in official statistics and survey production.
AStA Wirtschafts- und Sozialstatistisches Archiv 18. Oct. 2024. DOI
[9]
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
Multi-Accurate CATE is Robust to Unknown Covariate Shifts.
Transactions on Machine Learning Research. Oct. 2024. Certifications: Featured. URL
[8]
U. Fischer Abaigar • C. Kern • F. 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
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
[7]
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
Measurement Modeling of Predictors and Outcomes in Algorithmic Fairness.
EWAF 2024 - 3rd European Workshop on Algorithmic Fairness. Mainz, Germany, Jul 01-03, 2024. PDF
[6]
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
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
[5]
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
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
[4]
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
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
[3]
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
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
[2]
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
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
[1]
C. Kern • M. Kim • A. Zhou
Multi-CATE: Multi-Accurate Conditional Average Treatment Effect Estimation Robust to Unknown Covariate Shifts.
Preprint (May. 2024). arXiv
Multi-CATE: Multi-Accurate Conditional Average Treatment Effect Estimation Robust to Unknown Covariate Shifts.
Preprint (May. 2024). arXiv
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2024-12-27 - Last modified: 2026-04-10