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“Optical Random Features For Large-Scale Machine Learning,” Dr. Laurent Daudet, CTO & Co-Founder at LightOn

Date: February 5th, 2020

“Optical Random Features For Large-Scale Machine Learning”

Dr. Laurent Daudet, CTO & Co-Founder at LightOn, Professor at Paris Diderot University

Event Organized By:

IEEE Photonics Society of the IEEE Santa Clara Valley Section

Co-sponsors:

Registration Link: Here

PROGRAM:

6:00 – 6:30 PM Networking & Refreshments
6:30 – 7:45 PM Talk
7:45 – 8:00 PM Q&A/Adjourn

Abstract:

The propagation of coherent light through a scattering medium is an extremely complex physical process. However, under certain conditions, if the incoming beam is spatially modulated to encode some data, the output as measured on a sensor can be modeled as a random projection of the input, i.e. its multiplication by a random iid matrix. One can leverage this principle for compressive imaging, and more generally for any data processing pipeline involving large-scale random projections. This talk will discuss the theoretical foundations that led to the development of LightOn’s Optical Processing Unit (OPU), the world’s first optical AI chip already operational at scale – available through LightOn Cloud. I will finally present a series of OPU use cases for machine learning, such as transfer learning, change point detection, recommender systems, or reinforcement learning.

Bio:

As CTO at LightOn, Laurent’s task is to manage cross-disciplinary R&D projects, involving machine learning, optics, signal processing, electronics, and software engineering. Laurent is currently on leave from his position of Professor of Physics at Paris Diderot University, Paris. Prior to that or in parallel, he has held various academic positions: fellow of the Institut Universitaire de France, associate professor at Universite Pierre et Marie Curie, Visiting Senior Lecturer at Queen Mary University of London, UK, Visiting Professor at the National Institute for Informatics in Tokyo, Japan. Laurent has authored or co-authored nearly 200 scientific publications, has been a consultant to various small and large companies, and is a co-inventor in several patents. He is a graduate in physics from Ecole Normale Superieure in Paris, and holds a PhD in Applied Mathematics from Marseille University.

Venue:

Intel SC12 Auditorium, 3600 Juliette Ln, Santa Clara, CA 95054

Admission Fee:

All admissions free. Suggested donations to cover food and water:

Non-IEEE: $5, Students (non-IEEE): $3, IEEE Members (not members of CASS or SSCS): $3

Online registration is recommended to guarantee seating.

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