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 impacts. The theme invited speakers spanning academia, industry and government institutions.
This year’s theme focuses on two subtopics. One, how is machine learning being used to improve fabrication and manufacturing of optics or by optics, such as in laser manufacturing? The other subtopic examines solvers based on machine learning approaches. Through these talks, attendees will learn about the newest machine learning technologies applied to optics and photonics and compare them with conventional approaches.
Theme Coordinators
- Groot Gregory, Synopsys Inc., USA
- Chenkai Mao, Stanford University, USA
- Ben Mills, University of Southampton, UK
Visionary Speaker
Tyler Hughes, Flexcompute, USA
Talk Title: Building the Future of Photonic Design and Simulation with Machine Learning
Invited Speakers
David Brady, Univ. of Arizona, USA
Title to be Announced
Yijun (Joy) Ding, Synopsys, USA
Automated Design for Large and Manufacturable Metalenses
Priyanka Ghosh, MTC, UK
AI for High-Power Laser Based Manufacturing, Present and Future
Ighodalo Idehenre, US Air Force Reseach Lab/Core4ce, USA
Title to be Announced
Jan Kaster, Zeiss, Germany
Resolving Opto-Thermoelastic Perturbation Ambiguities with Design of Experiments and Gaussian Process Regression
Ziyi Lin, KronosAI, USA
Title to be Announced
Dylan McGuire, Ansys, Inc., Canada
Title to be Announced
Raphael Pestourie, Georgia Institute of Technology, USA
Title to be Announced
Martin Schubert, invrs.io, USA
Title to be Announced
Jiahui Wang, Google X, USA
Title to be Announced