Band-edge lasing in gold-clad photonic-crystal membranes. - Jan M. Van Campenhout; Peter Bienstman; Roel Baets (IEEE J. Sel. Areas Commun., 2005)

Python in Nanophotonics Research. - Peter Bienstman; Lieven Vanholme; Wim Bogaerts; Pieter Dumon; Peter Vandersteegen (Comput. Sci. Eng., 2007)

Photonic Reservoir Computing with Coupled Semiconductor Optical Amplifiers. - Kristof Vandoorne; Wouter Dierckx; Benjamin Schrauwen; David Verstraeten; Peter Bienstman; Roel Baets; Jan M. Van Campenhout (OSC, 2008)

Python Bindings for the Open Source Electromagnetic Simulator Meep. - Emmanuel Lambert; Martin Fiers; Shavkat Nizamov; Martijn Tassaert; Steven G. Johnson; Peter Bienstman; Wim Bogaerts (Comput. Sci. Eng., 2011)

Parallel Reservoir Computing Using Optical Amplifiers. - Kristof Vandoorne; Joni Dambre; David Verstraeten; Benjamin Schrauwen; Peter Bienstman (IEEE Trans. Neural Networks, 2011)

Improving the design cycle for nanophotonic components. - Martin Fiers; Emmanuel Lambert; Shibnath Pathak; Bjorn Maes; Peter Bienstman; Wim Bogaerts; Pieter Dumon (J. Comput. Sci., 2013)

Employing a dual polarisation microring to determine refractive index and thickness of a thin polymer layer. - Jan-Willem Hoste; Bruno G. De Geest; Peter Bienstman (ICTON, 2014)

Trainable and Dynamic Computing: Error Backpropagation through Physical Media. - Michiel Hermans; Michael Burm; Joni Dambre; Peter Bienstman (CoRR, 2014)

Nanophotonic Reservoir Computing With Photonic Crystal Cavities to Generate Periodic Patterns. - Martin Andre Agnes Fiers; Thomas Van Vaerenbergh; Francis Wyffels; David Verstraeten; Benjamin Schrauwen; Joni Dambre; Peter Bienstman (IEEE Trans. Neural Networks Learn. Syst., 2014)

Polymer microring resonators for biosensing applications by nanoimprint lithography. - R. Morarescu; P. K. Pal; X. Han; M. Zhao; Peter Bienstman; Geert Morthier (ICTON, 2015)

Neural network for blood cell classification in a holographic microscopy system. - Bendix Schneider; Geert Vanmeerbeeck; Richard Stahl; Liesbet Lagae; Joni Dambre; Peter Bienstman (ICTON, 2015)

Photonic reservoir computing approaches to nanoscale computation. - Andrew Katumba; Peter Bienstman; Joni Dambre (NANOCOM, 2015)

High performance photonic reservoir computer based on a coherently driven passive cavity. - Quentin Vinckier; François Duport; Anteo Smerieri; Kristof Vandoorne; Peter Bienstman; Marc Haelterman; Serge Massar (CoRR, 2015)

Photonic delay systems as machine learning implementations. - Michiel Hermans; Miguel C. Soriano; Joni Dambre; Peter Bienstman; Ingo Fischer (J. Mach. Learn. Res., 2015)

Optoelectronic Systems Trained With Backpropagation Through Time. - Michiel Hermans; Joni Dambre; Peter Bienstman (IEEE Trans. Neural Networks Learn. Syst., 2015)

An integrated Photonics Reservoir Computing approach to signal equalization for telecommunications. - Andrew Katumba; Bendix Schneider; Joni Dambre; Peter Bienstman (ICTON, 2016)

Silicon photonics: Silicon nitride versus silicon-on-insulator. - Roel Baets; Ananth Z. Subramanian; Stephane Clemmen; Bart Kuyken; Peter Bienstman; Nicolas Le Thomas; Gunther Roelkens; Dries Van Thourhout; Philippe Hélin; Simone Severi (OFC, 2016)

Using Digital Masks to Enhance the Bandwidth Tolerance and Improve the Performance of On-Chip Reservoir Computing Systems. - Bendix Schneider; Joni Dambre; Peter Bienstman (IEEE Trans. Neural Networks Learn. Syst., 2016)

On-Chip Passive Photonic Reservoir Computing with Integrated Optical Readout. - Matthias Freiberger; Andrew Katumba; Peter Bienstman; Joni Dambre (ICRC, 2017)

Reservoir computing with signal-mixing cavities. - Floris Laporte; Joni Dambre; Peter Bienstman (ICTON, 2017)

A Multiple-Input Strategy to Efficient Integrated Photonic Reservoir Computing. - Andrew Katumba; Matthias Freiberger; Peter Bienstman; Joni Dambre (Cogn. Comput., 2017)

Silicon Photonics Neuromorphic Computing and its Application to Telecommunications (Invited). - Andrew Katumba; Xin Yin; Joni Dambre; Peter Bienstman (ECOC, 2018)

Neuromorphic Computing with Signal-Mixing Cavities. - Floris Laporte; Joni Dambre; Peter Bienstman (ICRC, 2018)

Integrated Dielectric Scatterers for Speeding up Classification of Cell Diffraction Patterns. - Alessio Lugnan; Joni Dambre; Peter Bienstman (ICTON, 2018)

Photonic Resevoir Computing: A Brain-inspired Approach for Information Processing. - Peter Bienstman; Joni Dambre; Andrew Katumba; Matthias Freiberger; Floris Laporte; Alessio Lugnan (OFC, 2018)

A Power-Efficient Architecture for On-Chip Reservoir Computing. - Stijn Sackesyn; Chonghuai Ma; Andrew Katumba; Joni Dambre; Peter Bienstman (ICANN (Workshop), 2019)

All-Optical Readout for Integrated Photonic Reservoir Computing. - Chonghuai Ma; Stijn Sackesyn; Joni Dambre; Peter Bienstman (ICTON, 2019)

Addressing Limited Weight Resolution in a Fully Optical Neuromorphic Reservoir Computing Readout. - Chonghuai Ma; Floris Laporte; Joni Dambre; Peter Bienstman (CoRR, 2019)

Towards Deep Physical Reservoir Computing Through Automatic Task Decomposition And Mapping. - Matthias Freiberger; Peter Bienstman; Joni Dambre (CoRR, 2019)

Training Passive Photonic Reservoirs With Integrated Optical Readout. - Matthias Freiberger; Andrew Katumba; Peter Bienstman; Joni Dambre (IEEE Trans. Neural Networks Learn. Syst., 2019)

Threshold Plasticity of Hybrid Sİ-VO2 Microring Resonators. - Zhi Wang; Qiang Li; Ziling Fu; Andrew Katumba; Florian Denis-Le Coarer; Damien Rontani; Marc Sciamanna; Peter Bienstman (OFC, 2020)

Experimental Demonstration of Nonlinear fibre Distortion Compensation with Integrated Photonic Reservoir Computing. - Stijn Sackesyn; Chonghuai Ma; Joni Dambre; Peter Bienstman (ECOC, 2021)

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. - Kostas Sozos; Adonis Bogris; Peter Bienstman; Charis Mesaritakis (ECOC, 2021)

Computing with Integrated Photonic Reservoirs. - Joni Dambre; Andrew Katumba; Chonghuai Ma; Stijn Sackesyn; Floris Laporte; Matthias Freiberger; Peter Bienstman (Reservoir Computing, 2021)

High Speed Photonic Neuromorphic Computing Using Recurrent Optical Spectrum Slicing Neural Networks. - Kostas Sozos; Adonis Bogris; Peter Bienstman; George Sarantoglou; Stavros Deligiannidis; Charis Mesaritakis (CoRR, 2022)

Flow cytometry with event-based vision and spiking neuromorphic hardware. - Steven Abreu; Muhammed Gouda; Alessio Lugnan; Peter Bienstman (CVPR Workshops, 2023)

EUROPULS: NEUROmorphic energy-efficient secure accelerators based on Phase change materials aUgmented siLicon photonicS. - Fabio Pavanello; Cédric Marchand 002; Ian O'Connor; Régis Orobtchouk; Fabien Mandorlo; Xavier Letartre; Sébastien Cueff; Elena-Ioana Vatajelu; Giorgio Di Natale; Benoit Cluzel; Aurelien Coillet; Benoît Charbonnier; et al. (ETS, 2023)

Silicon Ring Resonator with Phase-Change Material as a Plastic Dynamical Node for Scalable All-Optical Neural Networks with Synaptic Plasticity. - Alessio Lugnan; Santiago Garcia-Cuevas Carrillo; Junchao Song; Samarth Aggarwal; Frank Brückerhoff-Plückelmann; Wolfram H. P. Pernice; Harish Bhaskaran; C. David Wright; Peter Bienstman (ICTON, 2023)

Numerical Analysis of a Self-Calibrating Time-Spatial Interleaving Photonic Convolutional Accelerator. - Tigers Jonuzi; Sarah Masaad; Alessandro Lupo; J. David Doménech Gomez; Peter Bienstman; Serge Massar (PSC, 2023)

Special Session: Neuromorphic hardware design and reliability from traditional CMOS to emerging technologies. - Fabio Pavanello; Elena-Ioana Vatajelu; Alberto Bosio; Thomas Van Vaerenbergh; Peter Bienstman; Benoît Charbonnier; Alessio Carpegna; Stefano Di Carlo; Alessandro Savino (VTS, 2023)

Training a spiking neural network on an event-based label-free flow cytometry dataset. - Muhammed Gouda; Steven Abreu; Alessio Lugnan; Peter Bienstman (CoRR, 2023)

NEUROPULS: NEUROmorphic energy-efficient secure accelerators based on Phase change materials aUgmented siLicon photonicS. - Fabio Pavanello; Cédric Marchand 002; Ian O'Connor; Régis Orobtchouk; Fabien Mandorlo; Xavier Letartre; Sébastien Cueff; Elena-Ioana Vatajelu; Giorgio Di Natale; Benoit Cluzel; Aurelien Coillet; Benoît Charbonnier; et al. (CoRR, 2023)

Invited: Neuromorphic Architectures Based on Augmented Silicon Photonics Platforms. - Matej Hejda; Federico Marchesin; George Papadimitriou 001; Dimitris Gizopoulos; Benoît Charbonnier; Régis Orobtchouk; Peter Bienstman; Thomas Van Vaerenbergh; Fabio Pavanello (DAC, 2024)

Clustering and Classification of Fungal Cells and PMMA Microparticles: Unsupervised and Supervised Learning using K-Means, PCA, Logistic Regression and Spiking Neural Networks on Event-Based Cytometry Datasets. - Muhammed Gouda; Steven Abreu; Peter Bienstman (ICTON, 2024)

Roadmap on Neuromorphic Photonics. - Daniel Brunner; Bhavin J. Shastri; Mohammed Al-Qadasi; Hitesh Ballani; Sylvain Barbay; Stefano Biasi; Peter Bienstman; Simon Bilodeau; Wim Bogaerts; Fabian Böhm; Grace Brennan; Sonia M. Buckley; et al. (CoRR, 2025)

How to Incorporate External Fields in Analog Ising Machines. - Robbe De Prins; Jacob Lamers; Peter Bienstman; Guy van der Sande; Guy Verschaffelt; Thomas Van Vaerenbergh (CoRR, 2025)