Dr Antonio Hurtado

Reader

Institute of Photonics

Personal statement

I am a Reader and Turing Artificial Intelligence (AI) Fellow with the Institute of Photonics, University of Strathclyde, Glasgow (UK). I completed my Ph.D. at the Universidad Politécnica de Madrid (UPM), Spain. I have more than 15 years of international research experience in photonics, having worked at the Universities of Essex and Strathclyde (UK), the University of New Mexico (USA) and UPM (Spain). I was the recipient of two Marie Curie Fellowships awarded by the European Commission, and a Chancellor’s Fellowship from the University of Strathclyde, following which I was appointed as a Lecturer at Strathclyde’s Institute of Photonics in 2014. At Strathclyde, I have established and lead the Neuromorphic Photonics research group and have been Principal Investigator in programmes funded by UK (e.g. EPSRC), US (e.g. ONRG) and EU (e.g. H2020 Programme) agencies. Notably, in 2020 I was awarded a Turing AI Acceleration Fellowship by the UK Research and Innovation (UKRI) Office and the UK Govt. Business, Energy and Industrial Strategy Dept., to develop a 5-year Programme on ‘Photonics for Ultrafast AI’.

Publications

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Publications

Polarization modulation in quantum-dot spin-VCSELs for ultrafast data transmission: Tselios Christos, Georgiou Panagiotis, Politi Christina, Hurtado Antonio, Alexandropoulos Dimitris; IEEE Journal of Quantum Electronics Vol 59, pp. 1-8 (2023); https://doi.org/10.1109/jqe.2023.3296732
Optically-triggered deterministic spiking regimes in nanostructure resonant tunnelling diode-photodetectors: Ali Al-Taai Qusay Raghib, Hejda Matěj, Zhang Weikang, Romeira Bruno, Figueiredo José M L, Wasige Edward, Hurtado Antonio; Neuromorphic Computing and Engineering Vol 3 (2023); https://doi.org/10.1088/2634-4386/acf609
Brain-inspired nanophotonic spike computing : challenges and prospects: Romeira Bruno, Adão Ricardo, Nieder Jana B, Al-Taai Qusay, Zhang Weikang, Hadfield Robert H, Wasige Edward, Hejda Matěj, Hurtado Antonio, Malysheva Ekaterina, Dolores Calzadilla Victor, Lourenço João, Castro Alves D, Figueiredo José M L, Ortega-Piwonka Ignacio, Javaloyes Julien, Edwards Stuart, Davies J Iwan, Horst Folkert, Offrein Bert J; Neuromorphic Computing and Engineering Vol 3 (2023); https://doi.org/10.1088/2634-4386/acdf17
Photonic spiking neural networks with highly efficient training protocols for ultrafast neuromorphic computing systems: Owen-Newns Dafydd, Robertson Joshua, Hejda Matěj, Hurtado Antonio; Intelligent Computing (2023); https://doi.org/10.34133/icomputing.0031
Spiking behaviour in laterally-coupled pairs of VCSELs with applications in neuromorphic photonics: Hejda Matĕj, Vaughan Martin, Henning Ian, Al-Seyab Rihab, Hurtado Antonio, Adams Mike; IEEE Journal of Selected Topics in Quantum Electronics Vol 29, pp. 1-10 (2023); https://doi.org/10.1109/jstqe.2022.3218950
Artificial optoelectronic spiking neuron based on a resonant tunnelling diode coupled to a vertical cavity surface emitting laser: Hejda Matěj, Malysheva Ekaterina, Owen-Newns Dafydd, Ali Al-Taai Qusay Raghib, Zhang Weikang, Ortega-Piwonka Ignacio, Javaloyes Julien, Wasige Edward, Dolores-Calzadilla Victor, Figueiredo José M L, Romeira Bruno, Hurtado Antonio; Nanophotonics Vol 12, pp. 857-867 (2023); https://doi.org/10.1515/nanoph-2022-0362

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Research

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Research Interests

My research interests lie within Photonics for Neuromorphic Computing and Artificial Intelligence (AI). This is a rapidly emerging scientific field combining concepts from diverse disciplines (e.g. photonics, neuroscience, computer science) seeking to emulate the brain’s powerful computational capabilities for new paradigms in light-enabled ultrafast brain-inspired computing and AI. I have established the Neuromorphic Photonics group at Strathclyde, which deliveres fundamental and impact-inspired research in this emerging field, with a main focus on novel ultrafast artificial photonic spking neurons, photonic spiking neural networks and optical spike-based processing platforms towards high-speed, energy-efficient, light-enabled, brain-inspired computing architectures.