Session 1: Raising the bar in Machine Learning: the photonic approach (90 min, 12 min per speaker + 18 min discussion)
Neuromorphic Photonics using Diffractive Optics and Lattice Filters, Folkert Horst, IBM Zurich, Switzerland
Universal Linear Optics in Neuromorphic Photonics, Apostolos Tsakyridis, Aristotle University of Thessaloniki, Greece
Multi-wavelength Silicon Photonic Neural Networks and Applications, Chaoran Huang, Princeton University, USA
Amplitude Modulation in Linear Optical Circuits for AI inference, Johannes Feldmann, Salience Labs, UK
Neuromorphic silicon photonics: inference and training, classical and quantum, Bhavin Shastri, Queens University, Canada
Photonic-electronic accelerators for machine intelligence, Volker Sorger, Optelligence, USA
Plenary discussion
Coffee Break (30 min)
Session 2: Photonic accelerators: thinking beyond machine learning (90 min, 12 min per speaker + 30 min discussion)
Solving Hard Optimization Problems with Light, George Mourgias-Alexandris, Microsoft Research, UK
Plug-and-play universal photonic processors for quantum information processing, Caterina Taballione, QuiX Quantum, Netherlands
Integrated microwave photonics PIC Platform: Realization of an optical beamformer, Chris Roeloffzen, LioniX, Netherlands
Programmable Photonics, Daniel Perez-Lopez, iPronics, Spain
Silicon Photonics in Programmable Linear Circuitry, Wim Bogaerts, imec, Belgium
Plenary discussion