Industry Program
18 - 21 August 2025
Hyatt Regency Seattle
Seattle, Washington UNITED STATES
Industry Program
The Industry Program at the Optica Imaging Congress enhances the engagement between attendees from academia, industry and government.
Background
This year, the Industry Program focuses on two key aspects in the contemporary imaging industry: human vision factors and machine learning. The knowledge of human vision factors is essential to design and optimize optics and imaging processing in consumer imaging products. It is also important to understand the potential and limitations of machine learning in the imaging process, especially for bio-medical applications.
Objectives
Join us to gain practical knowledge and learn the latest technologies and solutions from industry experts, network with experts and peers and stay ahead of the latest industry trends.
Industry Chairs
Lisa Belodoffa
Bell Collaborative, USA, Industry Chair
Francisco Imai
Apple Inc., USA, Industry Co-Chair
| Event name | Tuesday, 19 August | Wednesday, 20 August |
|---|---|---|
| Human Factors in Imaging | 18:00 - 19:00 | |
| Frontiers in Imaging - Trends in Machine Learning and Biological Imaging | 12:00 - 13:00 |
Human Factors in Imaging
Tuesday, 19 August 18:00 - 19:00
Moderator: Francisco Imai, Apple Inc., USA
The panel on “Human Factors in Imaging” will have experts in image quality and human vision from industry discussing about image quality in direct view and near-eye displays, key perceptual research questions, role of machine learning in visual perception, quantification of visual comfort in imaging systems and opportunities to create synergy between image visual perception research and optics.
Speakers
Alex Chapiro
Meta Reality Labs Research, UNITED STATES
Scott Daly
Dolby Laboratories, Inc.
Aaron Nicholls
Meta Reality Labs, UNITED STATES
Frontiers in Imaging - Trends in Machine Learning and Biological Imaging
Wednesday, 20 August 12:00 - 13:00
Moderator: Francisco Imai, Apple Inc., USA
Experts in image processing, machine learning and biological sciences discuss how machine learning can overcome limitations in optics in imaging systems, as well as trade-offs in applying machine learning to signal processing and inverse problems, potential issues of hallucinations in machine learning and on unsolved challenges in biological imaging.
Speakers
Mauricio Delbracio
Google LLC, UNITED STATES
Caleb Stoltzfus
Alpenglow Biosciences, UNITED STATES
