• Technical Conference:  23 – 26 September 2024
  • Science + Industry Showcase:   24 – 25 September 2024
  • Colorado Convention Center, Denver, Colorado, USA

Theme: Machine Learning

Machine Learning

The theme program provides an interdisciplinary platform to learn about and discuss a wide range of optics and photonics topics that machine learning has recently impacted. The theme features two Visionary Speakers and invited speakers spanning academia, industry and government institutions. 

These exciting speakers provide both historical retrospectives and state-of-the-art views on emerging machine learning techniques being applied to optics and photonics applications. The topics include computational imaging, metaphotonics, optical computing, biophotonics and many more. Through these talks, attendees will learn about the newest machine learning technologies applied to optics and photonics and some of the emerging concepts in embedding optical physics into machine learning-based designs.

Coordinator
Groot Gregory, Synopsys Inc., USA

Visionary Speaker
Peter McMahon, Cornell University, USA

Invited Speakers
Goery Genty, Tampere University, Finland

Ryoichi Horisaki, University of Tokyo, Japan
Computational Imaging with Randomness

Luzhe Huang, University of California, Los Angeles, USA
Self-Supervised, Experiment-Free Neural Network for Hologram Reconstruction Using Physics Consistency

Keisuke Kojima, Boston Quantum Photonics, USA
Photonics X Machine Learning

Zhaocheng Liu, Meta, USA
Synergy Between Machine Learning and Optical Physics for Expansive Design Space Exploration in Advanced Optical Design

Yuan Luo, National Taiwan University, Taiwan
Deep Learning for Flat Optics in Biomedical Applications

Shalin Mehta, Chan Zuckerberg Biohub, USA

Chris Metzler, University of Maryland, USA
Neural Wavefront Shaping

Tomoya Nakamura, Osaka University, Japan
Computational Coded Imaging Systems Using Trained/Untrained Neural Networks

Ilker Oguz, École Polytechnique Fédérale de Lausanne, Switzerland
Training Deep Optical Neural Networks With a Local Loss Function

Nakul Shekhawat, Johns Hopkins University, USA
Machine Learning in Ophthalmology: State of the Art and Future Directions

Simon Thibault, Université Laval, Canada
AI in and for Optical System Design: A Lens Designer Point of View