16:15 to 16:25
Welcome and Opening Remarks
Saša Bajt, Deutsches Elektronen-Synchrotron (Germany)
Pavel Bakule, ELI Beamlines (Czech Republic)
Optics + Optoelectronics Symposium Chairs

SPIE Presentation of the 2025 SPIE Maria Goeppert Mayer Award in Photonics
to

Pavel Cheben, National Research Council Canada

SPIE congratulates Pavel Cheben, Principal Research Officer at the National Research Council Canada, in recognition of his pioneering contributions to silicon photonic waveguide devices, including the invention of metamaterial waveguides and advancing sub-wavelength integrated photonics technology

Presentation of SPIE Fellowship
to
Niels Quack, Univ. of Sydney (Australia)
and
Peter D. Dragic, Univ. of Illinois (United States)


Plenary Speaker Introduction
Saša Bajt, Deutsches Elektronen-Synchrotron (Germany)
Pavel Bakule, ELI Beamlines (Czech Republic) Optics + Optoelectronics 2025 Symposium Chairs


16:25 to 17:10
TBA


Philip Walther, Univ. of Vienna (Austria)

Philip Walther is a Professor at the University of Vienna. His research group is dedicated to quantum information experiments and one of the leaders in photonic quantum computing. The group is developing photonic quantum technology, reaching from multi-photon sources to integrated waveguides and superconducting photon detectors for exploring new quantum physical features and to investigate the application of those for novel quantum-enhanced information processing. Recently, his research has also been covering experiments at the interface between quantum physics and gravity, where particular interferometers aim to probe the quantum superposition principle in combination with general relativity at the single-photon level.

17:15 to 18:00
Large-scale optical machine learning exploiting disorder


Sylvain Gigan, Sorbonne Univ. (France) and Lab. Kastler-Brossel, ENS (France)

Photonics is an ideal technology for low-energy and ultrafast information processing, and photonic computing is currently seeing a surge of interest, with exciting perspectives. In Machine Learning, optics is naturally well suited to implement a layer of neural networks, via either in integrated or free-space approaches. However, most proof-of-concepts of optical machine learning to date are limited to modest dimensions, single or relatively shallow artificial neural layer networks, and to relatively simple ML tasks.

I will show how multiple scattering of light allows performing optically an interesting operation for machine learning : large scale random matrix multiplication, I will present their application to various tasks, and discuss how we can extend this concept beyond single layers operations, and to modern machine learning tasks.


Sylvain Gigan is professor of physics at Sorbonne Université in Paris and group leader in Laboratoire Kastler-Brossel at Ecole Normale Supérieure. His research interests range from fundamental investigations of light propagation in complex media, biomedical imaging, computational imaging, and signal processing, to quantum optics and quantum information in complex media.

After graduating from Ecole Polytechnique (Palaiseau France) in 2000 and a Master specialization in optics from University Paris XI (Orsay, France), he obtained a PhD in physics in 2004 from University Pierre and Marie Curie (Paris, France) in quantum and non-linear Optics. From 2004 to 2007, he was a postdoctoral researcher in Vienna University (Austria). from 2007 to 2014, he was at ESPCI ParisTech as Associate Professor, and started working on optical imaging in complex media and wavefront shaping techniques, at the Langevin Institute.

Dr. Gigan is also the cofounder of a spin-off called LightOn (www.lighton.ai), aiming at performing optical computing for machine learning and big data. He was awarded the Fabry de Gramont Prize of the French Optical Society in 2016, The Joseph Fourier ATOS prize in 2018, the Jean Jerphagnon Prize in 2019. He was a member of the Institut Universitaire de France (2016-2021). He is Editor of Optics Communications.