Isabel Valera

Isabel Valera is a full Professor in the Department of Computer Science at Saarland University in Saarbrücken, Germany, and an Adjunct Faculty member at the Max Planck Institute for Software Systems (MPI-SWS). She is also a fellow of the European Laboratory for Learning and Intelligent Systems (ELLIS), contributing to the Robust Machine Learning Program and the Saarbrücken AI & ML (Sam) Unit.

• Department of Computer Science, Saarland University
• Adjunct Faculty, MPI for Software Systems
• ELLIS Fellow, Robust ML Program
• Sam Unit, Saarbrücken AI & ML

She obtained her PhD and MSc from Universidad Carlos III de Madrid, followed by postdoctoral research at the University of Cambridge and MPI for Software Systems. She previously led an independent research group at MPI for Intelligent Systems in Tübingen and held the Humboldt Post-Doctoral Fellowship and Minerva Fast Track Fellowship.

• PhD in Machine Learning, Universidad Carlos III de Madrid, 2014
• MSc in Multimedia and Communications, Universidad Carlos III de Madrid, 2012
• Telecommunications Engineering, Technical University of Cartagena, 2009

Her research centers on developing machine learning methods that are flexible, robust, interpretable, and fair, particularly for heterogeneous, temporal, and high-stakes decision-making systems. She emphasizes applications in medicine, psychiatry, and social domains such as hiring, bail, and lending. Her methodological contributions include Bayesian nonparametric models, latent feature modeling, and temporal point processes.

Her recent publications reflect a strong focus on fairness, robustness, and interpretability in machine learning. Key themes include latent feature modeling for mixed data types, clustering temporal event streams, source separation, and fair classification. Her work bridges theoretical innovation with practical applications across healthcare, social networks, and policy-relevant domains.

Scientific awards and recognitions include:

• Humboldt Post-Doctoral Fellowship
• Minerva Fast Track Fellowship (Max Planck Society)
• ELLIS Fellow

She has been actively involved in teaching and dissemination, delivering tutorials at NIPS and MLSS on temporal point processes and social network analysis. She has also supervised research assistants and mentored junior researchers. Her research has been supported through prestigious fellowships and institutional affiliations. She leads the development of open-source tools such as GLFM, HDHP, and iFDM, promoting reproducibility and accessibility in machine learning research.

She is affiliated with the following labs and research groups:

• Max Planck Institute for Intelligent Systems (former group leader)
• Max Planck Institute for Software Systems (adjunct, postdoctoral)
• ELLIS Sam Unit (Saarbrücken AI & ML)
• Robust Machine Learning Program (ELLIS)