andres masegosa

☰

“Chaos is merely order waiting to be deciphered.” José Saramago, Nobel Prize in Literature 1998.

[Download CV]

research interests

Trustworthy Machine Learning – Bayesian Methods – Uncertainty Quantification – Theoretical ML – Probability Theory – Probabilistic Modelling – Ensemble Methods – PAC-Bayes Theory

positions

  • 2021-. Associate professor, Department of Computer Science, Aalborg University (Copenhagen Campus – Denmark).
  • 2018–2021. Assistant professor, Department of Mathematics, University of Almería (Spain).
  • 2016–2018. Senior Researcher, Department of Mathematics, University of Almería (Spain).
  • 2014–2016. Post-Doc Researcher, Department of Computer Science, NTNU (Norway).
  • 2009–2013. Post-Doc Researcher, Department of Computer Science, University of Granada (Spain).
  • 2005–2009. PhD Student, Department of Computer Science, University of Granada (Spain).

scholarships, grants

  • 2026–2029 – Villum Synergy Programme. PI.
    DK-Future: Probabilistic Geospatial Machine Learning for Predicting Future Danish Land Use under Compound Climate Impact. 2 PDs. Funded with 4.5M DKK.

  • 2020–2022 – National Research Grant. Co-PI.
    Explainable Machine Learning: A Probabilistic Approach. Competitive National Call by the Spanish Ministry of Science. 1 PhD student. 62,000€.

  • 2019 – José Castillejo Scholarship. Highly competitive national call by the Spanish Ministry of Science.
    Funded with 15,000€ for a research visit at University of Copenhagen.

  • 2017–2018 – Early-Stage Researcher Grant. PI.
    Probabilistic Programming Languages for Intelligent Applications on Large Data. Competitive National Call (6% acceptance). 2 Post-Docs. Funded with 172,000€.

  • 2013 – Young Researcher Scholarship. Local Call (University of Granada).
    Discretization of Expression Quantitative Trait Loci using Machine Learning Models. Funded with 3,000€.

  • 2005–2009 – PhD Scholarship. Competitive National Call by the Spanish Ministry of Science. Funded with 96,000€.

international collaborations

  • Thomas D. Nielsen, Professor (MSO), Probabilistic ML, Aalborg University (Denmark).
  • Yevgeny Seldin, Professor, PAC-Bayes, University of Copenhagen (Denmark).
  • Christian Igel, Professor, Ensembles, University of Copenhagen (Denmark).
  • Helge Langseth, Professor, Temporal Data, NTNU (Norway).
  • Shinichi Nakajima, Senior Researcher, Clustering, TU Berlin (Germany).
  • Antonio D. Masegosa, IkerBasque Researcher, AutoML, University of Deusto (Spain).
  • Antonio Salmerón, Professor, Probabilistic Modelling, University of Almería (Spain).
  • Joaquín Abellán, Professor, Imprecise Probabilities, University of Granada (Spain).
  • Linda C. van der Gaag, Senior Researcher, Dalle Molle Institute for AI, Lugano (Switzerland).

invited keynotes

  • October 2023 – Keynote. International Workshop on the Mathematics of Deep Learning. BCAM, Bilbao (Spain).
  • December 2021 – Keynote. NeurIPS Workshop “Your Model is Wrong”. Online.

organisation of scientific meetings

  • June 2024 – ProbAI-2024 (Fifth Nordic Probabilistic AI School). 150 participants. Denmark.
  • June 2023 – ProbAI-2023 (Fourth Nordic Probabilistic AI School). 150 participants. Norway.

lecturing at international summer schools

  • June 2025 – Probabilistic AI Summer School (Trondheim, Norway).
  • June 2021 – Probabilistic AI Summer School (Helsinki, Finland).
  • June 2019 – Probabilistic AI Summer School (Trondheim, Norway).
  • October 2019 – Autumn School on Machine Learning (Tbilisi, Georgia).
  • June 2018 – Winter School on Practical AI (Geilo, Norway).

editorial board, program committee, reviewer

  • Area Coordinator: NeurIPS, ICML, AISTATS.
  • Area Editor: ACM Transactions on Probabilistic Machine Learning, Intelligent Data Analysis (IDA), Transactions on Machine Learning Research.
  • Program Committee: NeurIPS, ICML, ICLR, AISTATS.
  • Reviewer: JMLR, JAIR, Knowledge-Based Systems, IJAR, and others.

supervision of students and postdocs

  • 2023–. PhD co-supervisor. Thomas Hedge – Probabilistic ML.
  • 2023–. PhD co-supervisor. Ioar Casado – PAC-Bayes Bounds.
  • 2021–. PhD co-supervisor. Salomey Osegi – Ensembles & AutoML.
  • 2017–2018. PI and Post-Doc supervisor. Rafael Cabañas – Deep Probabilistic Models.
  • 2017–2018. PI and Post-Doc supervisor. Javier Cozar – Deep Probabilistic Models.

invited talks

  • Feb 2024 – D3A Conference for Robotics Workshop (Nyborg, Denmark).
  • May 2022 – Department of Computer Science, University of Copenhagen (Denmark).
  • Nov 2022 – D3A Conference – Theoretical ML Workshop (Nyborg, Denmark).
  • December 2021 – G-Research (Canada).
  • February 2021 – University of Cambridge, Department of Computer Science (UK).
  • November 2020 – Alan Turing Institute, Machine Learning Group (UK).
  • May 2022 – University of Copenhagen.
  • September 2019 – University of Copenhagen.
  • August 2018 – TU Berlin.
  • August 2017 – TU Berlin.
  • November 2016 – Apache Big Data Europe (Seville, Spain).

education

  • 2005–2009 – PhD in Computer Science. University of Granada (Spain).
  • 2003–2005 – Master in Soft Computing and Artificial Intelligence. University of Granada (Spain).
  • 1998–2003 – BSc Computer Engineering. University of Granada (Spain).