Please note that this website refers to a past event - for reference use only

The recent explosion of deep learning applications imposes an urgent need for new energy-efficient alternative neuromorphic hardware concepts running at high speeds and relying on a high degree of parallelism. In this workshop, we will explore this rapidly developing area of (classical) neuromorphic computing over a range of scalable platforms, both on a theoretical and experimental level. These platforms include systems in the domains of optics, integrated photonics, spin systems, semi- and superconducting systems, soft matter, and others. In addition, new physical learning approaches will be discussed.

Confirmed invited speakers

  • Firooz Aflatouni (U Penn)
  • Daniel Brunner (CNRS, FEMTO-ST)
  • Sonia Buckley (NIST)
  • Darius Bunandar (lightmatter)
  • Claudio Conti (Rome)
  • György Csaba (Budapest)
  • Sylvain Gigan (Paris)
  • Julie Grollier (CNRF Thales)
  • Alexander Khajetoorians (Radboud University)
  • Andrea Liu (U Penn)
  • Alexander Lvovsky (Oxford)
  • Tatsuhiro Onodera (Cornell)
  • Wolfram Pernice (Heidelberg)
  • Demetri Psaltis (EPFL)
  • Benjamin Scellier (Rain)
  • Johannes Schemmel (Heidelberg)
  • Abu Sebastian (IBM)
  • Menachem (Nachi) Stern (U Penn)


The in-person workshop will start on 5 September at 9 am and end on 7 September at approximately 5:30 pm. There will be invited talks, contributed talks, a poster session and a panel discussion. On Wednesday, we will organise a conference dinner which is included in the registration fee.

Click here for the workshop program.

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