Shining a Light on Machine Learning: Investigating the Intersection of Deep Learning and Optics - Barak Hadad

You are invited to attend a lecture on Tuesday, January 2, 2024, at 15:00

Wolfson Kitot building, Room 011

Shining a Light on Machine Learning: Investigating the Intersection of Deep Learning and Optics

Barak Hadad

Ph.D. student under the supervision of Prof. Alon Bahabad

Abstract

This study investigates the convergence of deep learning (DL) and optics, exploring the interdisciplinary applications at the intersection of physics and computer science. The research is divided into two sections.

The first section provides a survey of successful machine learning (ML) applications, with a specific focus on DL algorithms, in solving various optical problems. These applications span areas such as meta-material design, image reconstruction, and optical communications demultiplexing. By highlighting the effectiveness of ML techniques in optics, this section demonstrates their potential for addressing complex challenges in the field. The second section concentrates on the implementation of computational algorithms using optical systems to achieve faster and more parallel computing. Leveraging the distinctive characteristics of light and optics, novel approaches are explored to enhance the computational power and efficiency of DL algorithms. This section showcases how optical systems can enable more efficient and scalable DL computations.

By integrating DL algorithms into optical applications and fostering collaboration between optics and computer science, this research contributes to the development of innovative techniques and tools for tackling complex problems. The findings have implications for diverse fields, ranging from optical engineering to advanced computing