Lecture

Diffractive Deep Network: Optical Computing

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In course

MICRO-722: 3D Printing with light

Optical aspects of 3D printing technology. This includes optical systems for scanning and excitation, photopolymers, glass and other photoactive materials, and optical components fabricated with 3D printing technology. ...

Description

This lecture by the instructor covers the implementation of neural networks using diffractive layers and coherent light, focusing on optical computing. It explores the design of task-specific optical systems, all-optical machine learning, and diffractive optical neural networks. The presentation also includes experiments for classification, diffractive layers printing, and MNIST digit results.

Instructors (2)

Demetri Psaltis

Research group Teaching & PhD PhD Students Victoria Fay, Colin Nikhil Christian Past EPFL PhD Students Wuzhou Song, Alexandre Goy, Julien Cuennet, Ioannis Papadopoulos, Xin Yang, Grégoire Pierre Jean Laporte, Thomas Jean Victor Marie Lanvin, Seyyed Mohammad Hosseini Hashemi, Nicolino Stasio, Morteza Hasani Shoreh, Marilisa Romito, Pooria Hadikhani, Eirini Kakkava, Joowon Lim, Giulia Panusa, Ahmed Bassam Sayed Ayoub Mohamed Ayoub, Amirhossein Saba, Niyazi Ulas Dinç Past EPFL PhD

Christophe Moser

Dr. Christophe Moser is Associate Professor of Microengineering and Industrial Relations at the Swiss Federal Institute of Technology in Lausanne. He was the co-founder and CEO of Ondax,Inc for ten years prior to joining EPFL. During this decade, he raised $15 million from corporate and venture capital sources to fund volume production of thick holographic components in glass and develop devices enabled by these components such as tunable add-drop multiplexers for telecommunications, ultra-narrowband notch filters for low frequency Raman systems, high power semi-conductor frequency-narrowed pumps for fiber lasers, single frequency fixed and tunable lasers for sensing and femtosecond pulse compressors for micro-machining applications. Dr. Moser has a Ph.D. in Electrical Engineering from the California Institute of Technology, a minor in finance and a bachelor degree in Physics from EPFL. He is the co-inventor of 24 patents, 14 peer reviewed scientific publications, 9 IEEE proceedings and a book chapter. Private interests include tennis, running, ski, basketball and family excursions. 2010: Associate Professor, EPFL, faculty Science Technique Ingenieur. 2000-2010: co-founder, CEO Ondax, Inc. 1995-2000: Graduate Research Assistant, California Institute of Technology. 1993-1995: Engineering Project manager , TESA. 1988-1993: Bachelor candidate in Physics, EPFL. MAIN PUBLICATIONS:

Moser C., Havermeyer F,.Ultra-narrowband tunable laserline notch filter, Appl. Phys. B, 95 (3), pp 597-601, 2009.

Moser C. ,Ho L., Havermeyer F,. Self-aligned Non-dispersive External Cavity Tunable Laser, 16 (21), 16691-16696 Optics Express, 2008.

Steckman, GJ , Moser C. et al. Volume holographic grating wavelength stabilized laser diodes, IEEE J. Of Selected Topics in Quantum Electronics, (13), 672-678, 2007.

Buse K, Havermeyer F, Liu W., Moser C, Psaltis D. Holographic Filters , Book Chapter Photorefractive Materials and their Applications, 2005.

Havermeyer, F; Liu, WH; Moser, C, et al. Volume holographic grating-based continuously tunable optical filter , Opt. Eng. 43 (9), 2017-2021, 2004.

Moser C., Maravic I., Schupp B., Adibi A, Psaltis D, Diffraction efficiency of localized holograms in doubly doped LiNbO3 crystals, Opt. Lett. 25: (17),1243-1245, 2000.

Official source

Ontological neighbourhood

Information engineering

Machine learning: Artificial neural networks

Related concepts (32)

Printing

Printing is a process for mass reproducing text and images using a master form or template. The earliest non-paper products involving printing include cylinder seals and objects such as the Cyrus Cylinder and the Cylinders of Nabonidus. The earliest known form of printing as applied to paper was woodblock printing, which appeared in China before 220 AD for cloth printing. However, it would not be applied to paper until the seventh century.

Recurrent neural network

A recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.

Machine learning

Machine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.

Artificial neural network

Artificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.

Screen printing

Screen printing is a printing technique where a mesh is used to transfer ink (or dye) onto a substrate, except in areas made impermeable to the ink by a blocking stencil. A blade or squeegee is moved across the screen to fill the open mesh apertures with ink, and a reverse stroke then causes the screen to touch the substrate momentarily along a line of contact. This causes the ink to wet the substrate and be pulled out of the mesh apertures as the screen springs back after the blade has passed.

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