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Persoonlijk profiel

Quote

“Conjecturally, in the depths of the human brain runs an immensely powerful, simple, efficient and task- and signal-independent learning algorithm. It is my ultimate aim to use mathematics to uncover and develop such algorithms.”

Research profile

Jim Portegies is an Assistant Professor in the Applied Analysis group of the Centre for Analysis, Scientific computing and Applications (CASA) at Eindhoven University of Technology (TU/e). Jim Portegies works in the mathematical fields of analysis, measure theory and geometry, and applies techniques from these fields to problems in machine-learning and artificial intelligence. He has applied techniques from spectral geometry to prove guarantees on performance of nonlinear dimensionality reduction algorithms. Currently, he is investigating how to design algorithms that mimic how humans and animals learn.  

Despite the large number of recent advances in artificial intelligence, humans still outperform machines in many tasks. The central question of how to design machines that learn like humans is still wide open. The answer may lie in universal learning algorithms. Such algorithms are simple, efficient and can be applied to a broad variety of signals and tasks and are conjectured to exist in the depths of the human brain.

Academic background

Jim Portegies obtained his MSc in Industrial and Applied Mathematics and Applied Physics from the TU/e in 2009. He spent the 2007-2008 academic year as an exchange student at the University of Bonn, Germany. He received his PhD in Mathematics from the Courant Institute of Mathematical Sciences in New York. In the Fall of 2013, he spent a semester at NYU Shanghai, in Shanghai, China. After completing his PhD in 2014, he spent two years a postdoc at the Max Planck Institute for Mathematics in the Sciences in Leipzig, Germany until he returned to the TU/e as an assistant professor in Mathematics in 2016. Jim is a member of the TU/e Young Academy of Engineering. 

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Onderzoeksoutput

Learning for motion control in bonding machines: Bridging data-driven learning and physical modelling

Poot, M., Kostić, D., Vromans, R., Maleas, G., Portegies, J. & Oomen, T., 2 feb 2020, (Geaccepteerd/In druk).

Onderzoeksoutput: Bijdrage aan congresAbstractAcademic

Open Access
Bestand

Can VAEs capture topological properties?

Perez Rey, L. A., Menkovski, V. & Portegies, J. W., 2019.

Onderzoeksoutput: Bijdrage aan congresPaperAcademic

  • 5 Downloads (Pure)

    Total variation and mean curvature PDEs on the space of positions and orientations

    Duits, R., St-Onge, E., Portegies, J. & Smets, B., 5 jun 2019, Scale Space and Variational Methods in Computer Vision - 7th International Conference, SSVM 2019, Proceedings. Lellmann, J., Modersitzki, J. & Burger, M. (redactie). Berlin: Springer, blz. 211-223 13 blz. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11603 LNCS).

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

  • 3 Downloads (Pure)

    Asymptotic dependency structure of multiple signals: Asymptotic equipartition property for diagrams of probability spaces

    Matveev, R. & Portegies, J. W., dec 2018, In : Information Geometry. 1, 2, blz. 237-285

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

    Open Access
    Bestand
  • 41 Downloads (Pure)

    Continuity of nonlinear eigenvalues in CD (K, ∞) spaces with respect to measured Gromov–Hausdorff convergence

    Ambrosio, L., Honda, S. & Portegies, J. W., 1 apr 2018, In : Calculus of Variations and Partial Differential Equations. 57, 2, 34.

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

  • 1 Citaat (Scopus)
    3 Downloads (Pure)

    Cursussen

    Analysis 1

    1/09/12 → …

    Cursus

    Analysis 2

    1/09/12 → …

    Cursus

    Data analytics for engineers

    1/09/17 → …

    Cursus

    Scriptie

    A comparison of the Krasnoselskii spectrum and the homotopy significant spectrum

    Auteur: Fokma, S. (., 6 jul 2018

    Begeleider: Portegies, J. (Afstudeerdocent 1)

    Scriptie/masterproef: Bachelor

    Bestand

    Active learning in VAE latent space

    Auteur: Tonnaer, L., 25 sep 2017

    Begeleider: Menkovski, V. (Afstudeerdocent 1), Portegies, J. W. (Afstudeerdocent 2) & Holenderski, M. (Afstudeerdocent 2)

    Scriptie/masterproef: Master

    Bestand

    Computer programs for analysis

    Auteur: Beurskens, T. P., 1 jul 2019

    Begeleider: Portegies, J. W. (Afstudeerdocent 1)

    Scriptie/masterproef: Bachelor

    Bestand

    Convergence of several reinforcement learning algorithms

    Auteur: Mohamed, A., 29 okt 2018

    Begeleider: Portegies, J. W. (Afstudeerdocent 1)

    Scriptie/masterproef: Bachelor

    Bestand

    Differential equations driven by rough signals

    Auteur: Verstraelen, L. H., 31 aug 2018

    Begeleider: Prokert, G. (Afstudeerdocent 1) & Portegies, J. (Afstudeerdocent 2)

    Scriptie/masterproef: Bachelor

    Bestand