Bipin Rajendran

Bipin Rajendran

King's College

H-index: 37

North America-United States

About Bipin Rajendran

Bipin Rajendran, With an exceptional h-index of 37 and a recent h-index of 31 (since 2020), a distinguished researcher at King's College, specializes in the field of Nanoscale logic and memory devices, neuromorphic computation.

His recent articles reflect a diverse array of research interests and contributions to the field:

Energy-Efficient On-Board Radio Resource Management for Satellite Communications via Neuromorphic Computing

Towards Efficient and Trustworthy AI Through Hardware-Algorithm-Communication Co-Design

Ultra-Low Power Neuromorphic Obstacle Detection Using a Two-Dimensional Materials-Based Subthreshold Transistor

A Convolutional Spiking Network for Gesture Recognition in Brain-Computer Interfaces

Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticity

Spiking generative adversarial networks with a neural network discriminator: Local training, bayesian models, and continual meta-learning

Towards the Application of Neuromorphic Computing to Satellite Communications

Fast on-device adaptation for spiking neural networks via online-within-online meta-learning

Bipin Rajendran Information

University

Position

Reader in Engineering at

Citations(all)

9550

Citations(since 2020)

5377

Cited By

6273

hIndex(all)

37

hIndex(since 2020)

31

i10Index(all)

63

i10Index(since 2020)

50

Email

University Profile Page

King's College

Google Scholar

View Google Scholar Profile

Bipin Rajendran Skills & Research Interests

Nanoscale logic and memory devices

neuromorphic computation

Top articles of Bipin Rajendran

Title

Journal

Author(s)

Publication Date

Energy-Efficient On-Board Radio Resource Management for Satellite Communications via Neuromorphic Computing

IEEE Transactions on Machine Learning in Communications and Networking

Flor Ortiz

Nicolas Skatchkovsky

Eva Lagunas

Wallace A Martins

Geoffrey Eappen

...

2024/1/10

Towards Efficient and Trustworthy AI Through Hardware-Algorithm-Communication Co-Design

arXiv preprint arXiv:2309.15942

Bipin Rajendran

Osvaldo Simeone

Bashir M Al-Hashimi

2023/9/27

Ultra-Low Power Neuromorphic Obstacle Detection Using a Two-Dimensional Materials-Based Subthreshold Transistor

npj 2D Materials and Applications

Kartikey Thakar

Bipin Rajendran

Saurabh Lodha

2023

A Convolutional Spiking Network for Gesture Recognition in Brain-Computer Interfaces

Yiming Ai

Bipin Rajendran

2023

Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticity

Prabodh Katti

Nicolas Skatchkovsky

Osvaldo Simeone

Bipin Rajendran

Bashir M. Al-Hashimi

2023

Spiking generative adversarial networks with a neural network discriminator: Local training, bayesian models, and continual meta-learning

IEEE Transactions on Computers

Bleema Rosenfeld

Osvaldo Simeone

Bipin Rajendran

2022/7/18

Towards the Application of Neuromorphic Computing to Satellite Communications

Towards the Application of Neuromorphic Computing to Satellite Communications

Flor de Guadalupe Ortiz Gomez

Eva Lagunas

Wallace Alves Martins

Thinh Dinh

Nicolas Skatchkovsky

...

2022

Fast on-device adaptation for spiking neural networks via online-within-online meta-learning

Bleema Rosenfeld

Bipin Rajendran

Osvaldo Simeone

2021/6/5

Hybrid in-memory computing architecture for the training of deep neural networks

Vinay Joshi

Wangxin He

Jae-sun Seo

Bipin Rajendran

2021/5/22

An on-chip learning accelerator for spiking neural networks using stt-ram crossbar arrays

Shruti R Kulkarni

Shihui Yin

Jae-sun Seo

Bipin Rajendran

2020/3/9

ESSOP: Efficient and scalable stochastic outer product architecture for deep learning

Vinay Joshi

Geethan Karunaratne

Manuel Le Gallo

Irem Boybat

Christophe Piveteau

...

2020/10/12

Training multi-layer spiking neural networks using NormAD based spatio-temporal error backpropagation

Neurocomputing

Navin Anwani

Bipin Rajendran

2020/3/7

Accurate deep neural network inference using computational phase-change memory

Nature communications

Vinay Joshi

Manuel Le Gallo

Simon Haefeli

Irem Boybat

Sasidharan Rajalekshmi Nandakumar

...

2020/5/18

Experimental demonstration of supervised learning in spiking neural networks with phase-change memory synapses

Scientific reports

SR Nandakumar

Irem Boybat

Manuel Le Gallo

Evangelos Eleftheriou

Abu Sebastian

...

2020/5/15

Mixed-precision deep learning based on computational memory

Frontiers in neuroscience

SR Nandakumar

Manuel Le Gallo

Christophe Piveteau

Vinay Joshi

Giovanni Mariani

...

2020/5/12

Memristors—From in‐memory computing, deep learning acceleration, and spiking neural networks to the future of neuromorphic and bio‐inspired computing

Adnan Mehonic

Abu Sebastian

Bipin Rajendran

Osvaldo Simeone

Eleni Vasilaki

...

2020/11

Bio-mimetic synaptic plasticity and learning in a sub-500 mV Cu/SiO2/W memristor

Microelectronic Engineering

SR Nandakumar

Bipin Rajendran

2020/4/1

See List of Professors in Bipin Rajendran University(King's College)