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Jordi Vallverdú Segura

ICREA Acadèmia 2019

Universitat Autònoma de Barcelona · Humanities

Jordi Vallverdú Segura

Jordi Vallverdú, Ph.D., M.Sci., B.Mus, B.Phil  (Full Prof. accredited) is a Catalan investigator who has devoted his research to the cognitive and epistemic aspects of the Philosophy of Computing, Philosophy of Sciences, Cognition, and Philosophy of AI. After his Bachelor in Philosophy at U. Barcelona (1996), he obtained his M.Sci and Ph.D. at U. Autònoma de Barcelona (2001, 2002, respectively). He also obtained his Bachelor's in Music (ESMUC, 2011). He has had research stays at the Glaxo-Wellcome Institute for the History of Medicine (1997), J.F.K. School at Harvard University (2000), and Nishidalab at Kyoto University (2011, under a JSPS Grant). He has been visiting professor at Technische Universität München, and the University of Reading, and has been invited by a large number of institutions to lecture and teach specialized seminars. In 2019 won the Best presentation award at the HUAWEI Neuro-inspired, cognitive, and unconventional computing workshop, Kazan (Russia).




Research interests

Professor Vallverdú's research has been exploring two main related areas: epistemology and cognition. Since his early Ph.D. research on epistemic controversies, Prof. Vallverdú has analyzed several aspects of computational epistemology.

His latest research has been focused on the Causal challenges of  Machine Learning techniques, with special emphasis on Deep Learning. As one of the most promising advances, Statistics meets Causal graph reasoning (via Directed Acyclic Graphs), with several conceptual paths still to be explored and clearly identified. Counterfactual reasoning is a fundamental part of these open debates, which are under the analysis of Prof. Vallverdú.

His research has the support of: GEHUCT (2022-2024,  [2021 SGR 00517]), Tecnocog, and H2020-SwafS  CSI COP European Project (2020-2023).

Currently is finishing the book "Causality for Artificial Intelligence. From A Philosophical Perspective ", edited by Springer Editorial.








Epistemology, Deep Learning, Science,Statistics, Causality, Cognition, Heuristics

ICREA Memoir 2023