Shastri, Bhavin

Photonic and Neuromorphic Computing

Bavhin Shastri - Queen's University, Canada

Abstract
Artificial intelligence and combinatorial optimization problems—such as drug discovery and prime factorization—remain challenging even for supercomputers. We are addressing these limitations by building photonic processors inspired by the brain—photonic neural networks—which utilize light for faster and more energy-efficient processing. We will discuss photonic networks, including Ising machines enabled by silicon photonics and thin-film lithium niobate photonics, highlighting their applications in number partitioning, protein folding, wireless communications, and deep learning. Additionally, we will briefly introduce a quantum photonic neural network that can learn to act as near-perfect components of quantum technologies and discuss the role of weak 
nonlinearities.

References:
[1]    Shastri et al. Nature Photonics 15, 102–114 (2021)
[2]    S. Shekhar et al. Nature Communications 15, 751 (2024)
[3]    W. Zhang et al. Light: Science and Applications 13, 14 (2024)
[4]    C. Huang et al. Nature Electronics 4, 837–844 (2021)

Biography
Prof. Shastri is a Canada Research Chair, an Associate Professor of Engineering Physics at Queen’s University, and a Member of the College of the Royal Society of Canada. He is the Scientific Co-Director of NUCLEUS, a pan-Canadian photonic computing program. Dr. Shastri was named a 2025 Alfred P. Sloan Research Fellow in Physics and, in 2024, was recognized by Science News as one of its 10 Scientists to Watch. He received the 2022 SPIE Early Career Achievement Award and the 2020 Young Scientist Prize in Optics by the International Commission of Optics (ICO) “for his pioneering contributions to neuromorphic photonics”. He is a co-author of the book Neuromorphic Photonics (Taylor & Francis, 2017), a term he coined.