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Bhavin J. Shastri

Bhavin J. Shastri

D-Index & Metrics

Engineering and Technology

D-Index
44
Citations
10624
World Ranking
5706
National Ranking
228

Overview

Bhavin J. Shastri is affiliated with Queen's University in Canada and is active in the fields of engineering and computer science. Their research spans several subfields, with a particular focus on electrical and electronic engineering and artificial intelligence, supported by work in atomic and molecular physics, optics, biomedical engineering, and biophysics.

The scientist's primary topics of research include neural networks and reservoir computing, photonic and optical devices, optical network technologies, advanced memory and neural computing, advanced photonic communication systems, neural networks and applications, and advanced fiber laser technologies.

Bhavin J. Shastri has contributed to numerous publications in various scientific venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • IEEE Journal of Selected Topics in Quantum Electronics
  • Nanophotonics
  • Optica
  • Nature Communications

Some of the recent papers authored or co-authored by Bhavin J. Shastri include:

  • "Roadmapping the next generation of silicon photonics," 2024, Nature Communications
  • "Silicon photonic-electronic neural network for fibre nonlinearity compensation," 2021, arXiv (Cornell University)
  • "Roadmap on emerging hardware and technology for machine learning," 2020, Nanotechnology
  • "Silicon microring synapses enable photonic deep learning beyond 9-bit precision," 2022, Optica
  • "Demonstration of scalable microring weight bank control for large-scale photonic integrated circuits," 2020, APL Photonics

Collaboration forms a significant part of Bhavin J. Shastri's research work, with frequent co-authors including:

  • Paul R. Prucnal
  • Thomas Ferreira de Lima
  • Alexander N. Tait
  • Simon Bilodeau
  • Chaoran Huang

Best Publications

  • Photonics for artificial intelligence and neuromorphic computing

    Bhavin J. Shastri;Alexander N. Tait;Thomas Ferreira de Lima;Wolfram H. P. Pernice

  • Photonics for artificial intelligence and neuromorphic computing

    Bhavin J. Shastri;Bhavin J. Shastri;Alexander N. Tait;Alexander N. Tait;T. Ferreira de Lima;Wolfram H. P. Pernice

  • Neuromorphic photonic networks using silicon photonic weight banks.

    Alexander N. Tait;Thomas Ferreira de Lima;Ellen Zhou;Allie X. Wu

  • Roadmapping the next generation of silicon photonics

    Unknown

  • Broadcast and Weight: An Integrated Network For Scalable Photonic Spike Processing

    Alexander N. Tait;Mitchell A. Nahmias;Bhavin J. Shastri;Paul Richard Prucnal

  • A Leaky Integrate-and-Fire Laser Neuron for Ultrafast Cognitive Computing

    M. A. Nahmias;B. J. Shastri;A. N. Tait;P. R. Prucnal

  • A silicon photonic modulator neuron

    Alexander N. Tait;Thomas Ferreira de Lima;Mitchell A. Nahmias;Heidi B. Miller

  • Photonic Multiply-Accumulate Operations for Neural Networks

    Mitchell A. Nahmias;Thomas Ferreira de Lima;Alexander N. Tait;Hsuan-Tung Peng

  • A silicon photonic–electronic neural network for fibre nonlinearity compensation

    Chaoran Huang;Chaoran Huang;Shinsuke Fujisawa;Shinsuke Fujisawa;Thomas Ferreira de Lima;Alexander N. Tait

  • Recent progress in semiconductor excitable lasers for photonic spike processing

    Paul Richard Prucnal;Bhavin J. Shastri;Thomas Ferreira de Lima;Mitchell A. Nahmias

  • Neuromorphic Photonic Integrated Circuits

    Hsuan-Tung Peng;Mitchell A. Nahmias;Thomas Ferreira de Lima;Alexander N. Tait

  • NEUROMORPHIC PHOTONICS

    Unknown

  • Microring Weight Banks

    Alexander N. Tait;Allie X. Wu;Thomas Ferreira de Lima;Ellen Zhou

  • Digital Electronics and Analog Photonics for Convolutional Neural Networks (DEAP-CNNs)

    Viraj Bangari;Bicky A. Marquez;Heidi Miller;Alexander N. Tait

  • Neuromorphic Silicon Photonic Networks

    Alexander N. Tait;Thomas Ferreira de Lima;Ellen Zhou;Allie X. Wu

  • Progress in neuromorphic photonics

    Thomas Ferreira De Lima;Bhavin J. Shastri;Alexander N. Tait;Mitchell A. Nahmias

  • Machine Learning With Neuromorphic Photonics

    Thomas Ferreira de Lima;Hsuan-Tung Peng;Alexander N. Tait;Mitchell A. Nahmias

  • Spike processing with a graphene excitable laser.

    Bhavin J. Shastri;Mitchell A. Nahmias;Alexander N. Tait;Alejandro W. Rodriguez

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

    Unknown

  • Roadmap on emerging hardware and technology for machine learning.

    Karl Berggren;Qiangfei Xia;Konstantin K. Likharev;Dmitri B. Strukov

  • Feedback control for microring weight banks

    Alexander N. Tait;Hasitha Jayatilleka;Thomas Ferreira De Lima;Philip Y. Ma

  • ITO-based Electro-absorption Modulator for Photonic Neural Activation Function

    R. Amin;J. K. George;S. Sun;T. Ferreira de Lima

  • Prospects and applications of photonic neural networks

    Chaoran Huang;Chaoran Huang;Volker J. Sorger;Mario Miscuglio;Mohammed Al-Qadasi

  • Silicon Photonic Modulator Neuron

    Alexander N. Tait;Thomas Ferreira De Lima;Mitchell A. Nahmias;Heidi B. Miller

  • Neuromorphic photonics with electro-absorption modulators

    Jonathan George;Armin Mehrabian;Rubab Amin;Jiawei Meng

  • ITO-based Electro-absorption Modulator for Photonic Neural Activation Function

    Rubab Amin;Jonathan George;Shuai Sun;Thomas Ferreira de Lima

Frequent Co-Authors

Paul R. Prucnal
Paul R. Prucnal Princeton University
Alexander N. Tait
Alexander N. Tait Princeton University
Thomas Ferreira de Lima
Thomas Ferreira de Lima Princeton University
David V. Plant
David V. Plant McGill University
Volker J. Sorger
Volker J. Sorger George Washington University
Sudip Shekhar
Sudip Shekhar University of British Columbia
Lukas Chrostowski
Lukas Chrostowski University of British Columbia
Mable P. Fok
Mable P. Fok University of Georgia
Tarek El-Ghazawi
Tarek El-Ghazawi George Washington University
Leslie A. Rusch
Leslie A. Rusch Université Laval

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