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Photonic Reservoir ComputingResearch Area:
Neuromorphic computing enabled by integrated photonics Main Researcher: Peter Bienstman
Reservoir computing is a recently proposed methodology from the field of machine learning and neural networks, which has been used successfully in several pattern classification problems, like speech and image recognition. However, it has so far been used mainly in a software implementation, which limits its speed and power efficiency. Photonics could provide an excellent platform for such a hardware implementation, because of the presence of unique non-linear dynamics in photonics components due to the interplay of photons and electrons, and because light also has a phase in addition to an amplitude, which provides for an important additional degree of freedom as opposed to a purely electronic hardware implementation.
This research is supported by an ERC starting grant and happens in close collaboration with the Reservoir lab at the Elis department.
Other people involved: Related Research Projects
PhD thesises -
Kristof Vandoorne, Fotonisch Reservoir Computing met een netwerk van gekoppelde optische halfgeleiderversterkers, Photonic Reservoir Computing with a Network of Coupled Semiconductor Optical Amplifiers, (12/2011)
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Martin Fiers, Nanofotonische Reservoir Computing met fotonischekristalcaviteiten, Nanophotonic Reservoir Computing Using Photonic Crystal Cavities, (6/2013)
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Floris Laporte, Nieuwe architecturen voor brein-geinspireerde fotonische computers, Novel architectures for brain-inspired photonic computers, (3/2020)
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Alessio Lugnan, Op fotonica gebaseerd machinaal leren om labelvrije flowcytometrie te versnellen en te vereenvoudigen , Photonics-Based Machine Learning to Speed up and Simplify Label-Free Flow Cytometry , (9/2021)
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Emmanuel Gooskens, De golflengtedimensie in photonic reservoir computing, The Wavelength Dimension in Photonic Reservoir Computing, (5/2024)
Patents-
P. Bienstman, Joni dambre, K.T Vandoorne,
Reservoir computing using passive physical systems
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P. Bienstman, Liesbet Lagae, Geert Vanmeerbeeck, Joni Dambre, B. Schneider,
Holographic Device and Object Sorting System
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P. Bienstman, F. Laporte, A. Lugnan,
Mixing wave-based computing
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P. Bienstman, A. Lugnan, F. Laporte,
Object classification system and method
PublicationsInternational Journals
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S. Masaad, S. Sackesyn, Stylianos Sygletos, P. Bienstman,
Experimental Demonstration of 4-Port Photonic Reservoir Computing for Equalization of 4 and 16 QAM Signals, Journal of Lightwave Technologies, (2024).
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S. Masaad, P. Bienstman,
Opto-Electronic Machine Learning Network for Kramers-Kronig Receiver Linearization , Optics Express, (2024) .
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S. Abreu, I. Boikov, M. Goldmann, T. Jonuzi, A. Lupo, S. Masaad, L. Nguyen, E. Picco, G. Pourcel, A. Skalli, L. Talandier, B. Vettelschoss, E.A. Vlieg, A. Argyris, P. Bienstman, D. Brunner, J. Dambre, L. Daudet, J.D. Domenech, I. Fischer, F. Horst, S. Massar, C.R. Mirasso, B.J. Offrein, A. Rossi, M.C. Soriano, S. Sygletos, S.K. Turitsyn,
A photonics perspective on computing with physical substrates, accepted for publication in Reviews in Physics, (to be published) .
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E.J.C. Gooskens, S. Sackesyn, J. Dambre, P. Bienstman,
Experimental results on nonlinear distortion compensation using photonic reservoir computing with a single set of weights for different wavelengths, Scientific Reports, 13(21399), doi:doi.org/10.1038/s41598-023-48816-9 (2023) .
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C. Ma, J. Van Kerrebroeck, H. Deng, S. Sackesyn, E.J.C. Gooskens, B. Bai, J. Dambre, P. Bienstman,
Integrated photonic reservoir computing with an all-optical readout, Optics Express, 31(21), p.34843-34854 doi:https://doi.org/10.1364/OE.502354 (2023) .
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A. Lugnan, Santiago Garcia-Cuevas Carrillo, C. David Wright, P. Bienstman,
Rigorous dynamic model of a silicon ring resonator with phase change material for a neuromorphic node, Optics Express, 30(14), p.25177-25194 doi:10.1364/OE.459364 (2022) .
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E.J.C. Gooskens, F. Laporte, C. Ma, S. Sackesyn, P. Bienstman,
Wavelength Dimension in Waveguide-Based Photonic Reservoir Computing, Optics Express, 30(9), p.15634-15647 doi:10.1364/OE.455774 (2022).
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C. Ma, J. Lambrecht, F. Laporte, X. Yin, J. Dambre, P. Bienstman,
Comparing different nonlinearities in readout systems for optical neuromorphic computing networks, Scientific Reports , 11, p.24152 doi:https://doi.org/10.1038/s41598-021-03594-0 (2021) .
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S. Sackesyn, C. Ma, J. Dambre, P. Bienstman,
Experimental realization of integrated photonic reservoir computing for nonlinear fiber distortion compensation, Optics Express, 29(20), p.30991-30997 doi:10.1364/OE.435013 (2021) .
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Santiago Garcia-Cuevas Carrillo, A. Lugnan, Emanuele Gemo, P. Bienstman, Wolfram H. P. Pernice, Harish Bhaskaran, C. David Wright,
System-Level Simulation for Integrated Phase-Change Photonics, Journal of lightwave technology, 39(20), p. 6392 - 6402 doi:10.1109/JLT.2021.3099914 (2021) .
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C. Ma, F. Laporte, J. Dambre, P. Bienstman,
Addressing limited weight resolution in a fully optical neuromorphic reservoir computing readout, Scientific Reports, 11, p.article number 3102 (9 pages) doi:10.1038/s41598-021-82720-4 (2021) .
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F. Laporte, J. Dambre, P. Bienstman,
Simulating self-learning in photorefractive optical reservoir computers, Scientific Reports, 11, p.2701 doi:10.1038/s41598-021-81899-w (2021) .
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A. Lugnan, E.J.C. Gooskens, J. Vatin, J. Dambre, P. Bienstman,
Machine learning issues and opportunities in ultrafast particle classification for label‑free microflow cytometry, Scientific Reports, 10(1), p.1-13 doi:10.1038/s41598-020-77765-w (2020) .
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M. Freiberger, P. Bienstman, J. Dambre,
A training algorithm for networks of high-variability reservoirs, Scientific Reports, 10, p.1342 doi:10.1038/s41598-020-71549-y (2020) .
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D. Brunner, A. Marandi, W. Bogaerts, A. Ozcan,
Editorial: Photonics for computing and computing for photonics, Nanophotonics (invited), 9(13), p.4053-4054 doi:10.1515/nanoph-2020-0470 (2020) .
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M. Freiberger, A. Katumba, P. Bienstman, J. Dambre,
Training Passive Photonic Reservoirs with Integrated Optical Readout, IEEE Transactions on Neural Networks and Learning Systems, 30(7), p.1943-1953 doi:10.1109/tnnls.2018.2874571 (2019).
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F. Laporte, J. Dambre, P. Bienstman,
Highly parallel simulation and optimization of photonic circuits in time and frequency domain based on the deep-learning framework PyTorch, Scientific Reports, 9(1), p.5918 doi:10.1038/s41598-019-42408-2 (2019) .
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A. Katumba, X. Yin, J. Dambre, P. Bienstman,
A Neuromorphic Silicon Photonics Nonlinear Equalizer for Optical Communication with Intensity Modulation and Direct-Detection, Journal of Lightwave Technologies, 37(10), p.2232-2239 doi:10.1109/JLT.2019.2900568 (2019) .
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F. Denis-le Coarer, M. Sciamanna, A. Katumba, M. Freiberger, J. Dambre, P. Bienstman, D. Rontani,
All-optical reservoir computing on a photonic chip using silicon-based ring resonators, IEEE Journal on Selected Topics in Quantum Electronics, 24(6), doi:10.1109/JSTQE.2018.2836985 (2018).
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A. Katumba, M. Freiberger, F. Laporte, A. Lugnan, S. Sackesyn, C. Ma, J. Dambre, P. Bienstman,
Neuromorphic computing based on silicon photonics and reservoir computing, IEEE Journal on Selected Topics in Quantum Electronics (invited), 24(6), p.8300310 (10 pages) doi:10.1109/JSTQE.2018.2821843 (2018).
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F. Laporte, A. Katumba, J. Dambre, P. Bienstman,
Numerical demonstration of neuromorphic computing with photonic crystal cavities, Optics Express, 26(7), p.7955-7964 doi:10.1364/OE.26.007955 (2018) .
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A. Katumba, J. Heyvaert, B. Schneider, S. Uvin, J. Dambre, P. Bienstman,
Low-Loss Photonic Reservoir Computing with Multimode Photonic Integrated Circuits, Scientific Reports, 8(1), p.2653 doi:10.1038/s41598-018-21011-x (2018) .
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A. Lugnan, J. Dambre, P. Bienstman,
Integrated pillar scatterers for speeding up classification of cell holograms, Optics Express, 25(24), p.30526-30538 doi:10.1364/oe.25.030526 (2017) .
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A. Katumba, M. Freiberger, J. Dambre, P. Bienstman,
A Multiple-Input Strategy to Efficient Integrated Photonic Reservoir Computing, Cognitive Computation, 9(3), p.307-314 doi:10.1007/s12559-017-9465-5 (2017).
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Michiel Hermans, Miguel C. Soriano, J. Dambre, P. Bienstman, Ingo Fisher,
Photonic delay systems as machine learning implementations, Journal of Machine Learning Research, 16, p.2081-2097 (2015) .
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M. Fiers, T. Van Vaerenbergh, F. Wyffels, D. Verstraeten, B. Schrauwen, J. Dambre, P. Bienstman,
Nanophotonic reservoir computing with photonic crystal cavities to generate periodic patterns, IEEE Transactions on Neural Networks and Learning Systems, 25(2), p.344 - 355 doi:10.1109/tnnls.2013.2274670 (2014) .
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K. Alexander, T. Van Vaerenbergh, M. Fiers, P. Mechet, J. Dambre, P. Bienstman,
Excitability in optically injected microdisk lasers with phase controlled excitatory and inhibitory response, Optics Express, 21(22), p.26182-26191 doi:10.1364/oe.21.026182 (2013) .
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T. Van Vaerenbergh, J. Dambre, P. Bienstman, J.A. Levenson, A. Yacomotti,
Lumped circuit heat model of photonic crystal membrane nanocavities, IEEE Journal of Quantum Electronics, p.967 - 969 doi:10.1109/jqe.2013.2283576 (2013) .
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T. Van Vaerenbergh, K. Alexander, J. Dambre, P. Bienstman,
Excitation transfer between optically injected microdisk lasers, Optics Express, 21(23), p.28922-28932 doi:10.1364/oe.21.028922 (2013) .
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T. Van Vaerenbergh, M. Fiers, J. Dambre, P. Bienstman,
Simplified description of self-pulsation and excitability by thermal and free-carrier effects in semiconductor microcavities, Physical Review A, 86(6), p.063808 doi:10.1103/PhysRevA.86.063808 (2012) .
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T. Van Vaerenbergh, M. Fiers, P. Mechet, T. Spuesens, R. Kumar, G. Morthier, B. Schrauwen, J. Dambre, P. Bienstman,
Cascadable Excitability in microrings, Optics Express, 20(18), p.20292-20308 doi:10.1364/oe.20.020292 (2012) .
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M. Fiers, T. Van Vaerenbergh, K. Caluwaerts, D. Vande Ginste, B. Schrauwen, J. Dambre, P. Bienstman,
Time-domain and frequency-domain modeling of nonlinear optical components on circuit-level using a node-based approach, Journal of the Optical Society of America B, 29(5), p.896–900 doi:10.1364/josab.29.000896 (2012) .
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K.T Vandoorne, J. Dambre, D. Verstraeten, B. Schrauwen, P. Bienstman,
Parallel reservoir computing using optical amplifiers, IEEE Transactions on Neural Networks, 22(9), p.1469-1481 doi:10.1109/tnn.2011.2161771 (2011) .
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B. Maes, M. Fiers, P. Bienstman,
Self-pulsing and chaos in short chains of coupled nonlinear microcavities, Physical Review A, 80, p.033805 doi:10.1103/physreva.80.033805 (2009) .
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K.T Vandoorne, W. Dierckx, B. Schrauwen, D. Verstraeten, R. Baets, P. Bienstman, J. Van Campenhout,
Toward optical signal processing using Photonic Reservoir Computing, Optics Express, 16(15), p.11182-11192 doi:10.1364/oe.16.011182 (2008) .
Book / Book Chapter
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J. Dambre, A. Katumba, C. Ma, S. Sackesyn, M. Freiberger, P. Bienstman,
Computing with integrated photonic reservoirs, Reservoir Computing - Theory, Physical Implementations, and Applications, p.397-419 (2021) .
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A. Katumba, M. Freiberger, F. Laporte, A. Lugnan, S. Sackesyn, C. Ma, J. Dambre, P. Bienstman,
Integrated on-chip reservoirs, Photonic Reservoir Computing: Optical Recurrent Neural Networks (invited), p.53-82 (2019).
International Conferences
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S. Masaad, S. Sackesyn, Stylianos Sygletos, P. Bienstman,
Experimental Demonstration of 4-Port Photonic Reservoir Computing for Equalization of 4 and 16 QAM Signals, European Conference on Optical Communication, (2024).
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Y. Zhang, H. Deng, E. Soltanian, J. Zhang, G. Roelkens, W. Bogaerts,
A Nonlinear Activation Function for Optical Neural Networks Using a Mach-Zehnder Interferometer with a III-V-on-Si Amplifier, 2023 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC), Germany, doi:10.1109/CLEO/Europe-EQEC57999.2023.10231574 (2023) .
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E.J.C. Gooskens, S. Sackesyn, S. Masaad, J. Dambre, P. Bienstman,
Photonic Reservoir Computing for Wavelength Multiplexed Nonlinear Fiber Distortion Mitigation, IEEE SiPhotonics (formerly GFP conference), United States, p.1-2 doi:10.1109/SiPhotonics55903.2023.10141896 (2023) .
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S. Masaad, E.J.C. Gooskens, S. Sackesyn, J. Dambre, P. Bienstman,
Photonic Reservoir Computing for Nonlinear Equalization of 64-QAM Signals with a Kramers-Kronig Receiver, European Conference on Optical Communication, Tu4G.3 , Switzerland, (2022) .
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S. Sackesyn, S. Masaad, C. Ma, P. Bienstman,
Reservoir Computing with Optical Weights, European Conference on Optical Communication: Workshop on Photonic and Electronic Cointegration Solutions (WS13) (invited), Switzerland, (2022).
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E.J.C. Gooskens, F. Laporte, S. Sackesyn, C. Ma, P. Bienstman,
Wavelength Multiplexing in Photonic Reservoir Computing, Annual Symposium of the IEEE Photonics Society Benelux Chapter, (2021) .
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P. Bienstman, J. Dambre, A. Lugnan, S. Sackesyn, C. Ma, E.J.C. Gooskens, M. Gouda, S. Masaad,
Photonic Neuromorphic Computing Using Silicon Chips, Huawei STW (invited), (2021).
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A. Lugnan, S. Sackesyn, C. Ma, E.J.C. Gooskens, M. Gouda, S. Masaad, J. Dambre, P. Bienstman,
Reservoir computing for high-speed photonic information processing, Photonics in Switching and Computing (invited), p.TuA2.3 (2021) .
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S. Sackesyn, C. Ma, J. Dambre, P. Bienstman,
Experimental Demonstration of Nonlinear Fibre Distortion Compensation with Integrated Photonic Reservoir Computing, ECOC, France, p.SC3-tu4g.6 doi:10.1109/ECOC52684.2021.9606162 (2021) .
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K. Sozos, A. Bogris, P. Bienstman, C. Mesaritakis,
Photonic Reservoir Computing based on Optical Filters in a Loop as a High Performance and Low-Power Consumption Equalizer for 100 Gbaud Direct Detection Systems, ECOC, France, p.SC3-tu4g.3 doi:10.1109/ECOC52684.2021.9606123 (2021) .
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G. Van der Sande, F. Bohm, K. Harkhoe, J. Pauwels, P. Bienstman, T. Van Vaerenbergh, G. Verschaffelt,
Time-multiplexed optical systems for reservoir computing and coherent Ising machines, Nanoscience + Engineering, p.118041Q doi:10.1117/12.2594700 (2021) .
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A. Lugnan, S. Sackesyn, C. Ma, E.J.C. Gooskens, M. Gouda, S. Masaad, Joni Dambre, P. Bienstman,
Photonic reservoir computing for high-speed neuromorphic computing applications, 2021 IEEE Summer Topicals Meeting Series (invited), Mexico, (2021).
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S. Phang, D. Furniss, C. Mellor, G. Roelkens, A.B. Seddon, P. Bienstman, T. Benson,
Neuromorphic sensing via temporal signal signature processed by photonic reservoir computer, Photonics West, doi:10.1117/12.2584187 (2021).
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P. Bienstman, J. Dambre, A. Lugnan, S. Sackesyn, C. Ma, E.J.C. Gooskens, M. Gouda, S. Masaad,
Silicon photonics for brain-inspired neuromorphic information processing, 1st Workshop on Neuromorphic Photonics (invited), (2020) .
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F. Laporte, A. Katumba, M. Freiberger, A. Lugnan, S. Sackesyn, C. Ma, E.J.C. Gooskens, J. Dambre, P. Bienstman,
Photonic Reservoir Computing, Photonic Integration Week (invited), Spain, (2020).
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S. Sackesyn, C. Ma, A. Katumba, F. Denis-le Coarer, J. Dambre, P. Bienstman,
A power-efficient architecture for silicon photonic reservoir computing, Proceedings of the 24rd Annual Symposium of the IEEE Photonics Benelux Chapter, Netherlands, p.4 (2019) .
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S. Sackesyn, C. Ma, A. Katumba, J. Dambre, P. Bienstman,
A power-efficient architecture for on-chip reservoir computing, Artificial Neural Networks and Machine Learning ICANN 2019: Workshop and Special Sessions. ICANN 2019. Lecture Notes in Computer Science, 11731, Germany, p.161-164 doi:10.1007/978-3-030-30493-5_16 (2019).
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F. Laporte, J. Dambre, P. Bienstman,
Photontorch: Simulation and Optimization of Large Photonic Circuits Using the Deep Learning Framework PyTorch, IEEE Photonics Society Summer Topicals, United States, p.paper WE1.2 doi:10.1109/phosst.2019.8794941 (2019) .
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C. Ma, S. Sackesyn, J.Dambre, P. Bienstman,
All-Optical Readout for Integrated Photonic Reservoir Computing, 2019 21st International Conference on Transparent Optical Networks (ICTON) (invited), France, p.paper Fr.D5.4 (4 pages) doi:10.1109/ICTON.2019.8840492 (2019).
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M. Freiberger, P. Bienstman, J. Dambre,
Improving Time Series Prediction with Ensembles of Integrated Photonic Reservoirs, Cognitive Computing 2018: Merging Concepts with Hardware, Germany, p.2 (2018) .
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S. Sackesyn, C. Ma, J. Dambre, P. Bienstman,
An enhanced architecture for silicon photonic reservoir computing, Cognitive Computing 2018: Merging Concepts with Hardware, Germany, (2018) .
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K. Harkhoe, G. Verschaffelt, A. Katumba, P. Bienstman, G. Van der Sande,
Delay Based Reservoir Computing on Integrated InP Photonic Chip, Cognitive Computing: Merging Concepts with Hardware, Germany, p.2 (2018).
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C. Ma, F. Laporte, S. Sackesyn, J.Dambre, P. Bienstman,
Optical readout for low resolution weighting and easy observation for integrated photonic reservoir computing, accepted for publication in IEEE Benelux Chapter Annual Symposium 2019, (to be published).
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A. Lugnan, J. Dambre, P. Bienstman,
Numerical investigation of integrated dielectric pillars to simplify machine learning classification of cells, 23rd Annual Symposium of the IEEE Photonics Benelux Chapter, Belgium, (2018) .
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K. Harkhoe, G. Verschaffelt, A. Katumba, P. Bienstman, G. Van der Sande,
Integrated Delay Based Photonic Reservoir Computing, Proceedings of the 23rd Annual Symposium of the IEEE Photonics Benelux Chapter, Belgium, (2018).
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F. Laporte, J. Dambre, P. Bienstman,
Neuromorphic Computing with Signal-Mixing Cavities, IEEE International Conference on Rebooting Computing, United States, doi:10.1109/icrc.2018.8638622 (2018).
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A. Katumba, X. Jin, J. Dambre, P. Bienstman,
Silicon Photonics Neuromorphic Computing and its Application to Telecommunications, 44th European Conference on Optical Communication (invited), Italy, p.paper Mo4H (3 pages) doi:10.1109/ecoc.2018.8535262 (2018) .
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G. Van der Sande, K. Harkhoe, A. Katumba, P. Bienstman, G. Verschaffelt,
Semiconductor lasers with delayed optical feedback for reservoir computing: short external cavities and multi-mode lasers, International Conference on Control of Self-Organizing Nonlinear Systems (invited), Germany, p.9 (2018) .
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A. Lugnan, J. Dambre, P. Bienstman,
Integrated dielectric scatterers for speeding up classification of cell diffraction patterns, 2018 20th International Conference on Transparent Optical Networks (ICTON) (invited), Romania, p.We.A6.3, 4pp. doi:10.1109/ICTON.2018.8473611 (2018) .
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F. Denis-le Coarer, D. Rontani, A. Katumba, M. Freiberger, J. Dambre, P. Bienstman, M. Sciamanna,
Toward neuro-inspired computing using a small network of micro-ring resonators on an integrated photonic chip, SPIE PHOTONICS EUROPE, 10689, France, p.1068908-9 doi:10.1117/12.2306780 (2018).
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A. Lugnan, J. Dambre, P. Bienstman,
Integrated dielectric scatterers for fast optical classification of biological cells, SPIE Photonics Europe, 10689(07), France, p.1-7 doi:10.1117/12.2306654 (2018) .
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P. Bienstman, J. Dambre, A. Katumba, M. Freiberger, F. Laporte, A. Lugnan,
Photonic reservoir computing: a brain-inspired approach for information processing, The Optical Fiber Communication Conference (OFC) (invited), United States, p.paper M4F.4 (3 pages) doi:10.1364/OFC.2018.M4F.4 (2018).
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P. Bienstman, J. Dambre, A. Katumba, M. Freiberger, F. Laporte, A. Lugnan,
Silicon photonics for neuromorphic information processing , SPIE Photonics West (invited), DL 10551, United States, p.paper 10551-19 (7 pages) doi:10.1117/12.2284391 (2018).
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D. Rontani, F. Denis-Le Coarer, A. Katumba, M. Freiberger, J. Dambre, P. Bienstman, M. Sciamanna,
Reservoir Computing with Nonlinear Micro-Resonators on a Silicon Photonics Chip, International Symposium on Nonlinear Theory and Its Applications, Mexico, p.paper 5192, session A3LC (2017) .
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M. Freiberger, A. Katumba, J. Dambre, P. Bienstman,
On-chip passive photonic reservoir computing with integrated optical readout, ICRC2017, the IEEE International Conference on Rebooting Computing 2017, United States, p. 255 - 258 doi:10.1109/ICRC.2017.8123673 (2017).
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A. Katumba, M. Freiberger, J. Heyvaert, J. Dambre, P. Bienstman,
Building Scalable Integrated Silicon Photonics Reservoirs for Signal Processing, Frontiers in Optics, United States, p.paper JTu2A.92 (2 pages) doi:10.1364/FIO.2017.JTu2A.92 (2017).
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F. Laporte, J. Dambre, P. Bienstman,
Reservoir Computing with signal-mixing cavities, 19th International Conference on Transparent Optical Networks (ICTON) (invited), Spain, p.We.A5.3 doi:10.1109/ICTON.2017.8024990 (2017).
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A. Lugnan, J. Dambre, P. Bienstman,
Integrated pillar scatterers for speeding up classification of cell holograms through a RC-like machine learning approach, Workshop on Dynamical Systems and Brain-inspired Information Processing, Belgium, (2017) .
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A. Katumba, M. Freiberger, J. Dambre, P. Bienstman,
Passive integrated photonics reservoir computing with on-chip readout for telecommunication applications, Dynamical Systems and Brain Inspired Computing 2017 (invited), Belgium, (2017).
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A. Katumba, P. Bienstman, J. Dambre,
Photonic reservoir computing for telecom applications, Dynamical systems and brain-‐inspired information processing, France, (2015).
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A. Katumba, P. Bienstman, J. Dambre,
Photonic reservoir computing approaches to nanoscale computation, International Conference on Nanoscale Computing and Communication (NANOCOM, United States, doi:10.1145/2800795.2800827 (2015) .
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T. Van Vaerenbergh, M. Fiers, J. Dambre, P. Bienstman,
An optical delayline based on excitable microrings, IEEE Photonics Conference, United States, p.118-119 doi:10.1109/ipcon.2014.6995240 (2014) .
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T. Van Vaerenbergh, M. Fiers, J. Dambre, P. Bienstman,
Simulation of nonlinear optical resonator circuits, NUSOD 2014, Spain, p.103-104 doi:10.1109/nusod.2014.6935377 (2014) .
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T. Van Vaerenbergh, M. Fiers, J. Dambre, P. Bienstman,
Towards integrated optical spiking neural networks: delaying spikes on chip, Laser Dynamics and Nonlinear Photonics, 2013 Sixth "Rio De La Plata" Workshop on (invited), 1, Uruguay, p.9-12 doi:10.1109/LDNP.2013.6777418 (2013).
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P. Bienstman, K.T Vandoorne, T. Van Vaerenbergh, M. Fiers, B. Schneider, B. Schrauwen, J. Dambre,
Using silicon nanophotonics for digital and analog signal processing with reservoir computing, Progress In Electromagnetics Research Symposium (PIERS 2013) (invited), Sweden, p.64 (2013) .
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Q. Vinckier, F. Duport, A. Smerieri, K.T Vandoorne, P. Bienstman, M. Haelterman, S. Massar,
Conception et realisation d'un ordinateur analogique tout optique de type "reservoir" a l’aide d’une cavite optique lineaire passive fonctionnant en lumiere coherente, Horizons de l'optique, France, p.3 (2013) .
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P. Bienstman, K.T Vandoorne, T. Van Vaerenbergh, M. Fiers, B. Schneider, B. Schrauwen, J. Dambre,
Using silicon nanophotonics for digital and analog signal processing with reservoir computing, Horizons de l'optique (invited), France, p.12 (2013) .
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T. Van Vaerenbergh, M. Fiers, P. Mechet, T. Spuesens, R. Kumar, G. Morthier, K.T Vandoorne, B. Schneider, B. Schrauwen, J. Dambre, P. Bienstman,
Characterization of cascadable excitability in a silicon-on-insulator microring, Proceedings of the 2012 Annual Symposium of the IEEE Photonics Society Belenux Chapter, Belgium, p.119-122 (2012) .
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B. Schneider, J. Dambre, P. Bienstman,
Reduction of analogue bandwidth requirement in photonic on-chip reservoir computing , Proceedings of the 2012 Annual Symposium of the IEEE Photonics Society Benelux Chapter, Belgium, p.227-230 (2012) .
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T. Van Vaerenbergh, M. Fiers, P. Mechet, T. Spuesens, R. Kumar, G. Morthier, K.T Vandoorne, B. Schneider, B. Schrauwen, J. Dambre, P. Bienstman,
Self-pulsation and excitability mechanism in silicon-on-insulator microrings , 2012 Asia Communications and Photonics Conference (ACP), China, p.ATh4B.5 doi:10.1364/ACP.2012.ATh4B.5 (2012).
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M. Fiers, K.T Vandoorne, T. Van Vaerenbergh, J. Dambre, B. Schrauwen, P. Bienstman,
Optical Information Processing: Advances in Nanophotonic Reservoir Computing , International Conference on Transparent Optical Networks (invited), United Kingdom, doi:10.1109/icton.2012.6253889 (2012) .
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M. Fiers, T. Van Vaerenbergh, K. Caluwaerts, J. Dambre, P. Bienstman,
CAPHE: Time-domain and Frequency-domain Modeling of Nonlinear Optical Components, Advanced Photonics Congress, 2012 OSA, United States, p.paper IM2B.3 doi:10.1364/iprsn.2012.im2b.3 (2012) .
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T. Van Vaerenbergh, M. Fiers, K.T Vandoorne, B. Schneider, J. Dambre, P. Bienstman,
Towards a photonic spiking neuron: excitability in a silicon-on-insulator microring., 2012 International symposium on Nonlinear Theory and its Applications, Proceedings (NOLTA), Spain, p.767 - 770 doi:10.15248/proc.1.767 (2012) .
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K.T Vandoorne, T. Van Vaerenbergh, M. Fiers, P. Bienstman, D. Verstraeten, B. Schrauwen, J. Dambre,
Photonic reservoir computing and information processing with coupled semiconductor optical amplifiers, Fifth ‘RIO DE LA PLATA’ Workshop on Laser Dynamics and Nonlinear Photonics (invited), Uruguay, p.1-3 doi:10.1109/LDNP.2011.6162079 (2011) .
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K.T Vandoorne, D. Verstraeten, B. Schrauwen, J. Dambre, P. Bienstman,
Delays in photonic reservoir computing with semiconductor optical amplifiers, IEEE Photonics Benelux Chapter Annual Symposium, Belgium, (2011) .
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K.T Vandoorne, M. Fiers, T. Van Vaerenbergh, D. Verstraeten, B. Schrauwen, J. Dambre, P. Bienstman,
Advances in photonic reservoir computing on an integrated platform, International Conference on Transparent Optical Networks (ICTON) (invited), Sweden, p.Mo.B5.5 doi:10.1109/icton.2011.5970791 (2011) .
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K.T Vandoorne, M. Fiers, D. Verstraeten, B. Schrauwen, J. Dambre, P. Bienstman,
Optical signal processing with a network of semiconductor optical amplifiers in the context of photonic reservoir computing, SPIE Photonics West - OPTO, 7942, United States, p.79420P doi:10.1117/12.874165 (2011) .
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K.T Vandoorne, J. Dambre, D. Verstraeten, B. Schrauwen, P. Bienstman,
Delays in photonic reservoir computing with Semiconductor Optical Amplifiers, IEEE Photonics Benelux Chapter Annual Symposium, Netherlands, p.25-28 (2010) .
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K.T Vandoorne, M. Fiers, D. Verstraeten, B. Schrauwen, J. Dambre, P. Bienstman,
Photonic Reservoir Computing: a New Approach to Optical Information Processing, Workshop on "Cognitive and neural models for automated processing of speech and text" 2010 (CONAS), Belgium, (2010) .
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K.T Vandoorne, M. Fiers, D. Verstraeten, B. Schrauwen, J. Dambre, P. Bienstman,
Photonic Reservoir Computing: a New Approach to Optical Information Processing, International Conference on Transparent Optical Networks 2010 (ICTON) (invited), Germany, p.Th.A4.3 doi:10.1109/icton.2010.5548990 (2010) .
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B. Maes, M. Fiers, K. Huybrechts, G. Morthier, P. Bienstman,
Dynamics and Instabilities in Series of Coupled Nonlinear Resonators, ICTON 2009 (invited), Portugal, p.We.C4.3 doi:10.1109/icton.2009.5185249 (2009) .
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K.T Vandoorne, W. Dierckx, B. Schrauwen, D. Verstraeten, P. Bienstman, R. Baets, J. Van Campenhout,
Photonic reservoir computing with coupled semiconductor optical amplifiers, First International Workshop on Optical Supercomputing (OSC 2008), LNCS 5172, Austria, p.46-55 doi:10.1007/978-3-540-85673-3_4 (2008) .
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K.T Vandoorne, P. Bienstman,
A photonic implementation of reservoir computing, 12th Annual Symposium of the IEEE/LEOS Benelux Chapter, Belgium, p.195-198 (2007) .
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K.T Vandoorne, P. Bienstman,
A photonic implementation of reservoir computing, Proceedings Workshop of the IEEE/LEOS Benelux Chapter, Netherlands, p.25-26 (2007) .
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K.T Vandoorne, P. Bienstman, R. Baets,
A Photonic Implementation of Reservoir Computing, ePIXnet Winter School - Applications of Photonic Integration, Switzerland, p.65 (2007) .
National Conferences
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P. Bienstman, J. Dambre, A. Lugnan, S. Sackesyn, C. Ma, E.J.C. Gooskens, M. Gouda, S. Masaad,
Photonic Neuromorphic Computing Using Silicon Chips, BePOM (invited), (2021) .
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T. Van Vaerenbergh, M. Fiers, K.T Vandoorne, J. Dambre, P. Bienstman,
Photonic Reservoir Computing using thermal nonlinearities in microrings, 12th FEA PhD Symposium, (2011) .
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K.T Vandoorne, P. Bienstman,
Photonic reservoir computing with SOAs and delays, FirW Doctoraatssymposium, Belgium, p.139 (2010) .
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