Isabel Valera
Isabel Valera is a machine learning researcher whose work connects probabilistic models with fair decision systems. She earned an MSc in 2012 and a PhD in 2014 at Universidad Carlos III de Madrid, and coauthored a Bayesian model for psychiatric-disorder comorbidity. A Humboldt postdoctoral fellowship at MPI-SWS came in 2015; she published on preference-based fairness in 2017 and took over the Probabilistic Learning group at MPI-IS in 2019. She became a professor at Saarland University in 2020 and received an ERC Starting Grant in 2022 for Society-Aware Machine Learning, whose funded period began in 2023 and whose project aims to account for business goals, user benefit, and societal risk in ML development. She coauthored a 2022 paper on fair causal recourse; as of October 2026, she is a professor at Saarland, adjunct faculty at MPI-SWS, and an ELLIS Fellow.
Timeline
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2012–2014
An MSc, PhD and Bayesian model
She earns an MSc in 2012 and a PhD in 2014 at Universidad Carlos III de Madrid. In 2014, she coauthors a Bayesian nonparametric model to analyze psychiatric-disorder comorbidity.
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2015
A Humboldt postdoctoral fellowship
She receives a Humboldt Post-doctoral Fellowship in 2015, hosted by the Max Planck Institute for Software Systems in Germany.
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2017
Preference-based fairness in classification
In 2017, she coauthors “From Parity to Preference-based Notions of Fairness in Classification,” a paper that proposes preference-based fairness concepts drawn from fair division and envy-freeness.
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July 2019
Leading the Probabilistic Learning Group
In July 2019, she takes over the independent Probabilistic Learning Research Group at the Max Planck Institute for Intelligent Systems in Tübingen.
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April 2020
Professor at Saarland
She starts as a professor of computer science at Saarland University in April 2020. Her research focuses on machine learning and fair algorithms.
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2022
Society-Aware Machine Learning
She receives an ERC Starting Grant for Society-Aware Machine Learning in 2022. The project begins its funded period in 2023 and aims to account for business goals, user benefit, and societal risk across machine-learning development.
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2022
Fairness in causal recourse
She coauthors the 2022 AAAI paper “On the Fairness of Causal Algorithmic Recourse,” which proposes fairness criteria that account for causal links between features.
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As of October 2026
Professor and group leader
As of October 2026, she is a professor of machine learning at Saarland University, adjunct faculty at MPI-SWS, and a Fellow of ELLIS. She leads the probabilistic machine learning group and teaches the Machine Learning course in 2026.
Sources and credits
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- Isabel Valera – Machine Learning
- Bayesian Nonparametric Comorbidity Analysis of Psychiatric Disorders
- Dr. Isabel Valera Martinez
- [1707.00010] From Parity to Preference-based Notions of Fairness in Classification
- Isabel Valera appointed Group Leader of the new independent Probabilistic Learning Group at the Max Planck Institute for Intelligent Systems | Cyber Valley
- 4.5 million euros in EU funding for Saarbrücken computer science research
- 4.5 million euros in EU funding for Saarbrücken computer science research - Saarland Informatics Campus
- Funding – Machine Learning
- On the Fairness of Causal Algorithmic Recourse | Proceedings of the AAAI Conference on Artificial Intelligence
- Isabel Valera | European Laboratory for Learning and Intelligent Systems
- (Probabilistic) Machine Learning Group, Saarland University
- Machine Learning (SS 2026)