{
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    "api_type": "NWO Projects API",
    "version": "1.0.2",
    "licence": {
      "name": "CC0 1.0 Universal",
      "url": "https://creativecommons.org/publicdomain/zero/1.0",
      "description": "To the extent possible under law, all copyright and related or neighbouring rights have been waived worldwide to the data made available through this API."
    },
    "documentation": "https://doi.org/10.5281/zenodo.14918287",
    "release_date": "2025-08-20T00:00:00",
    "funder": "https://doi.org/10.13039/501100003246",
    "ror_id": "https://ror.org/04jsz6e67",
    "date": "2026-11-05T00:00:00",
    "count": 1,
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    "pages": 1,
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  },
  "projects": [
    {
      "project_id": "NGF.1708.25.009",
      "title": "Spiking Photonic ICs with Quantum-enhanced Efficiency for Neuromorphic Edge Processing (SPIKE-Q)",
      "funding_scheme_id": 5011,
      "funding_scheme": "NGF - Photon Delta PhotonDelta Photonic Technologies 2024 / 2025",
      "department": "Toegepaste en Technische Wetenschappen",
      "sub_department": "Toegepaste en Technische Wetenschappen",
      "start_date": "2026-03-16T00:00:00",
      "reporting_year": 2025,
      "summary_nl": "De wereld beweegt zich richting real-time kunstmatige intelligentie aan de rand van systemen, van slimme sensoren tot autonome systemen, maar de huidige elektronische processors verbruiken te veel energie en bereiken hun grenzen. SPIKE-Q stelt een nieuwe oplossing voor door herseninspiratie te combineren met fotonische chips die informatie verwerken met licht in plaats van elektriciteit. Door het ontwikkelen van ultrasensitieve en energie-efficiënte lichtgebaseerde detectorneuronen zal SPIKE-Q snellere en duurzamere AI mogelijk maken die direct aan de rand van systemen kan opereren. Dit project zal baanbrekende technologieën ontwikkelen voor de bouw van compacte, energiezuinige systemen voor toekomstige slimme apparaten, sensoren en AI-toepassingen.",
      "summary_en": "The world is moving toward real-time artificial intelligence at the edge of systems, from smart sensors to autonomous systems, but today's electronic processors consume too much energy and are reaching their limits. SPIKE-Q proposes a new solution by combining brain-inspired computing with photonic chips that process information using light instead of electricity. By developing ultra-sensitive and energy-efficient light-based detector neurons, SPIKE-Q will enable faster, greener AI that can run directly at the edge of systems. This project will pioneer new technology for building compact, low-power systems for future smart devices, sensors, and AI applications.",
      "award_amount": 729515,
      "grant_id": "https://doi.org/10.61686/KGBZY03842",
      "project_members": [
        {
          "role": "Main Applicant",
          "member_id": 528128,
          "last_name": "Dolores Calzadilla",
          "degree_pre_nominal": "dr.",
          "initials": "V.M.",
          "first_name": "Victor",
          "organisation": "Technische Universiteit Eindhoven - Eindhoven University of Technology||Faculteit Electrical Engineering - Department of Electrical Engineering||Eindhoven Hendrik Casimir Institute||Photonic Integration (PHI)",
          "organisation_id": 80663,
          "ror": "https://ror.org/02c2kyt77",
          "active": true
        },
        {
          "role": "Project leader",
          "member_id": 528128,
          "last_name": "Dolores Calzadilla",
          "degree_pre_nominal": "dr.",
          "initials": "V.M.",
          "first_name": "Victor",
          "organisation": "Technische Universiteit Eindhoven - Eindhoven University of Technology||Faculteit Electrical Engineering - Department of Electrical Engineering||Eindhoven Hendrik Casimir Institute||Photonic Integration (PHI)",
          "organisation_id": 80663,
          "ror": "https://ror.org/02c2kyt77",
          "active": true
        }
      ]
    }
  ]
}