activity
20192026
most citedProspects and applications of photonic neural networks

181 citations · 560 across the 17 of their papers we have counts for

collaborators

17 papers

physics.optics2026

Towards Terabit//s Multidimensional Silicon Photonic Engine

Hao Chen, Zengqi Chen, Wu Zhou +7

Increasing artificial intelligence (AI) workloads drive co-packaged optics (CPO), which integrates optical engines with electronic components. Optical interconnects can extend tran…

physics.optics2025

Large-scale artificial intelligence with 41 million nanophotonic neurons on a metasurface

Mingcheng Luo, Meirui Jiang, Bhavin J. Shastri +8

Conventional integrated circuits (ICs) struggle to meet the escalating demands of artificial intelligence (AI). This has sparked a renewed interest in an unconventional computing p…

cs.ET2025★ 18 cited

Roadmap on Neuromorphic Photonics

Daniel Brunner, Bhavin J. Shastri, Mohammed A. Al Qadasi +147

This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementatio…

physics.optics2024★ 2 cited

Online training and pruning of multi-wavelength photonic neural networks

Jiawei Zhang, Weipeng Zhang, Tengji Xu +5

CMOS-compatible photonic integrated circuits (PICs) are emerging as a promising platform in artificial intelligence (AI) computing. Owing to the compact footprint of microring reso…

physics.optics2024★ 1 cited

Fully integrated hybrid multimode-multiwavelength photonic processor with picosecond latency

Ahmed Khaled, A. Aadhi, Chaoran Huang +2

High-speed signal processing is essential for maximizing data throughput in emerging communication applications, like multiple-input multiple-output (MIMO) systems and radio-freque…

physics.optics2024★ 1 cited

Control-free and efficient integrated photonic neural networks via hardware-aware training and pruning

Tengji Xu, Weipeng Zhang, Jiawei Zhang +8

Integrated photonic neural networks (PNNs) are at the forefront of AI computing, leveraging on light's unique properties, such as large bandwidth, low latency, and potentially low…

physics.optics2022★ 1 cited

Multi-Wavelength Photonic Neuromorphic Computing for Intra and Inter-Channel Distortion Compensations in WDM Optical Communication Systems

Benshan Wang, Thomas Ferreira de Lima, Bhavin J Shastri +2

DSP (digital signal processing) has been widely applied in optical communication systems to mitigate signal distortions and has become one of the key technologies that have sustain…

eess.SP2022★ 65 cited

Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation

Weipeng Zhang, Alexander Tait, Chaoran Huang +6

The expansion of telecommunications incurs increasingly severe crosstalk and interference, and a physical layer cognitive method, called blind source separation (BSS), can effectiv…

physics.app-ph2022★ 1 cited

Design Automation of Photonic Resonator Weights

Thomas Ferreira de Lima, Eli A. Doris, Simon Bilodeau +8

Neuromorphic photonic processors based on resonator weight banks are an emerging candidate technology for enabling modern artificial intelligence (AI) in high speed, analog systems…

physics.optics2022

Nanophotonic cavity based synapse for scalable photonic neural networks

Aashu Jha, Chaoran Huang, Thomas Ferriera deLima +3

The bandwidth and energy demands of neural networks has spurred tremendous interest in developing novel neuromorphic hardware, including photonic integrated circuits. Although an o…

physics.app-ph2021★ 21 cited

Silicon photonic-electronic neural network for fibre nonlinearity compensation

Chaoran Huang, Shinsuke Fujisawa, Thomas Ferreira de Lima +12

In optical communication systems, fibre nonlinearity is the major obstacle in increasing the transmission capacity. Typically, digital signal processing techniques and hardware are…

physics.optics2021★ 69 cited

Photonic spiking neural networks and CMOS-compatible graphene-on-silicon spiking neurons

Aashu Jha, Chaoran Huang, Hsuan-Tung Peng +2

Spiking neural networks are known to be superior over artificial neural networks for their computational power efficiency and noise robustness. The benefits of spiking coupled with…

eess.SP2021★ 6 cited

A Photonic-Circuits-Inspired Compact Network: Toward Real-Time Wireless Signal Classification at the Edge

Hsuan-Tung Peng, Joshua Lederman, Lei Xu +5

Machine learning (ML) methods are ubiquitous in wireless communication systems and have proven powerful for applications including radio-frequency (RF) fingerprinting, automatic mo…

cs.ET2021★ 181 cited

Prospects and applications of photonic neural networks

Chaoran Huang, Volker J. Sorger, Mario Miscuglio +13

Neural networks have enabled applications in artificial intelligence through machine learning, and neuromorphic computing. Software implementations of neural networks on convention…

physics.app-ph2021★ 163 cited

Silicon microring synapses enable photonic deep learning beyond 9-bit precision

Weipeng Zhang, Chaoran Huang, Hsuan-Tung Peng +6

Deep neural networks (DNN) consist of layers of neurons interconnected by synaptic weights. A high bit-precision in weights is generally required to guarantee high accuracy in many…

physics.app-ph2020★ 4 cited

A Laser Spiking Neuron in a Photonic Integrated Circuit

Mitchell A. Nahmias, Hsuan-Tung Peng, Thomas Ferreira de Lima +4

There has been a recent surge of interest in the implementation of linear operations such as matrix multipications using photonic integrated circuit technology. However, these appr…

physics.app-ph2019★ 27 cited

Programmable Silicon Photonic Optical Thresholder

Chaoran Huang, Thomas Ferreira de Lima, Aashu Jha +4

We experimentally demonstrate an all-optical programmable thresholder on a silicon photonic circuit. By exploiting the nonlinearities in a resonator-enhanced Mach-Zehnder interfero…