POST-DIGITAL
POST-DIGITAL POST-DIGITAL: NEUROMORPHIC COMPUTING IN PHOTONIC AND OTHER NONLINEAR MEDIA

  • I.P.: Ingo Fischer, Claudio Mirasso
  • Partners: CSIC, UBFC, U Groningen, ULB, IBM, LightOn, VLC Photonics, IMEC, Thales
  • Pàgina web: https://postdigital.astonphotonics.uk
  • Data d'inici: 1 de abril de 2020
  • Data de finalització: 31 de març de 2024

POST-DIGITAL is a Marie Skłodowska-Curie Innovative Training Network, funded by the European Union’s Horizon 2020 research and innovation programme.
POST-DIGITAL is committed to form a new generation of engineers and researchers, affording them with a uniquely broad interdisciplinary education and training which enables them to design and develop unconventional computing systems which, for the first time, pass over the threshold of real-world exploitability and which thereby help Europe’s ICT landscape to master the transformation out of the impending crises of digital technologies.
POST-DIGITAL brings together fourteen leading academic and industrial players (including IBM, Thales and three highly reputed SMEs) in optical and neuromorphic computing, already connected in long-standing collaboration networks. These groups will now join forces in order to train through ground breaking research, complimentary skills training and industrial secondments fifteen high calibre early-stage researchers to become backbone innovators in a technology domain that is crucial for Europe’s sustained competitiveness in ICT scenarios facing a dramatic pressure for fundamental re-thinking.

Investigadors

  • Ingo Fischer

    Ingo Fischer

  • Claudio Mirasso

    Claudio Mirasso

  • Apostolos Argyris

    Apostolos Argyris

  • Miguel C. Soriano

    Miguel C. Soriano

  • Mirko Goldmann

    Mirko Goldmann

  • Lucas Talandier

    Lucas Talandier

Publicacions recents

56 GBaud PAM-4 100 km transmission system with photonic processing schemes

Estébanez, Irene; Li, Shi; Schwind, Janek; Fischer, Ingo; Pachnicke, Stephan; Argyris, Apostolos
Journal of Lightwave Technology 40, 1, 55-62 (2022)

Information Processing Capacity of a Single-Node Reservoir Computer: An Experimental Evaluation

Vettelschoss, Benedikt; Röhm, André; Soriano, Miguel C.
IEEE Transactions on Neural Networks and Learning Systems , (2021)

Analog information processing with time-multiplexed optoelectronic systems

Goldmann, Mirko; Fischer, Ingo; Soriano, Miguel C.
Emerging Topics in Artificial Intelligence (ETAI) 2021, International Society for Optics and Photonics, 11804, 118041X (2021)

Exploiting transient dynamics of a time-multiplexed reservoir to boost the system performance

Goldmann, Mirko; Mirasso, Claudio R.; Fischer, Ingo; Soriano, Miguel C.
International Joint Conference on Neural Networks 2021, IEEE Computational Intelligence Society, International Neural Network Society, , (2021)

Predicting hidden structure in dynamical systems

Gauthier, Daniel J.; Fischer, Ingo
Nature Machine Intelligence 3, 281–282 (2021)

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