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Mr. Alessio Lugnan  (Doctoral Researcher)

This person is working in this group since 2016.
Affiliation: Ghent University - IMEC
Department of Information Technology
Address: Technologiepark-Zwijnaarde 126
9052 Ghent
Office: iGent, Office 140.012
Phone: +32 492062776
E-mail: Alessio.Lugnan@UGent.be
ORCID: https://orcid.org/0000-0002-6587-2614
Research Area: Neuromorphic computing, photonics, machine learning
Promotors: Peter Bienstman and Joni Dambre
AlessioLugnan
Alessio Lugnan joined the Photonics Research Group (Ghent University / Imec) in November 2016 as a PhD student. He has been working on optical solutions for machine learning classification of cells and particles for imaging microflow cytometry and on integrated photonic reservoir computing using ring resonators. He received a Master's degree in Experimental Physics from the University of Trento.

Specific Research Topics

Patents

Publications (17)

    International Journals

  1. 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)  Download this Publication (2MB).
  2. A. Lugnan, A. Katumba, F. Laporte, M. Freiberger, S. Sackesyn, C. Ma, E.J.C. Gooskens, J. Dambre, P. Bienstman, Photonic neuromorphic information processing and reservoir computing, APL Photonics (invited), 5, p.020901 doi:10.1063/1.5129762 (2020)  Download this Publication (2.9MB).
  3. 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).
  4. 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)  Download this Publication (3MB).
    Book / Book Chapter

  1. A. Katumba, M. Freiberger, F. Laporte, A. Lugnan, S. Sackesyn, C. Ma, J. Dambre, P. Bienstman, Integrated on-chip reservoirs, (invited) publication in Photonic Reservoir Computing: Optical Recurrent Neural Networks ,  (to be published).
    International Conferences

  1. 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).
  2. P. Bienstman, J. Dambre, A. Katumba, M. Freiberger, F. Laporte, A. Lugnan, S. Sackesyn, C. Ma, E.J.C. Gooskens, Non-linear signal equalisation using silicon photonic reservoir computing, ECOC machine learning workshop (invited), Ireland, (2019).
  3. P. Bienstman, J. Dambre, A. Katumba, M. Freiberger, F. Laporte, A. Lugnan, S. Sackesyn, C. Ma, Neuromorphic information processing using silicon photonics, SPIE Optics and Photonics (invited), United States, p.11081-54 doi:10.1117/12.2524707 (2019)  Download this Publication (254KB).
  4. P. Bienstman, J. Dambre, A. Katumba, M. Freiberger, F. Laporte, A. Lugnan, S. Sackesyn, C. Ma, E.J.C. Gooskens, Silicon photonics reservoir computing at 32 Gbit/s, 5th Workshop on Dynamical Systems and Brain-Inspired Information Processing (invited), Germany, (2019).
  5. 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)  Download this Publication (524KB).
  6. 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)  Download this Publication (771KB).
  7. 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)  Download this Publication (636KB).
  8. 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).
  9. 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).
  10. F. Laporte, A. Lugnan, J. Dambre, P. Bienstman, Novel photonic reservoir computing architectures, Workshop on Dynamical Systems and Brain-inspired Information Processing, , Germany, (2017)  Download this Publication (372KB).
  11. A. Katumba, F. Laporte, A. Lugnan, J. Dambre, P. Bienstman, Integrated-photonics implementation of reservoir computing neural networks, Machine learning workshop at ECOC (invited), Sweden, (2017).
  12. 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)  Download this Publication (556KB).
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