Bipin Rajendran
Email: bipin.rajendran@kcl.ac.uk
Phone: +44 020 784 80607
Office: S2.45
Mailing address:
Department of Engineering,
King's College London,
Strand, London WC2R 2LS.
I am a Professor of Intelligent Computing Systems in the Department of Engineering at King's College London. I lead the King's Laboratory for Intelligent Computing (KLIC) and co-lead the Centre for Intelligent Information Processing (CIIPS).
I am interested in the following topics:
Biomimetic engineering & computation
Architectures and systems for intelligent computing
Novel materials & devices for next-generation computing applications
Algorithms and Analytics for urban challenges
News:
1/2024: A paper (in collaboration with the group of Osvaldo Simeone and Symeon Chatzinotas) is published in IEEE Transactions on Machine Learning in Communications and Networking, 2024:
F. Ortiz, N. Skatchkovsky, E. Lagunas, W. A. Martins, G. Eappen, S. Daoud, O. Simeone, B. Rajendran, S. Chatzinotas, On-Board Radio Resource Management for Satellite Communications via Neuromorphic Computing.
9/2023: A paper (in collaboration with the group of Saurabh Lodha) is published in npj 2D Materials and Applications 2023:
K. Thakar, B. Rajendran & S. Lodha, Ultra-Low Power Neuromorphic Obstacle Detection Using a Two-Dimensional Materials-Based Subthreshold Transistor.
4/2023: A paper from my group is accepted for publication in IEEE AICAS 2023:
Y. Ai, & B. Rajendran, A Convolutional Spiking Network for Gesture Recognition in Brain-Computer Interfaces.
1/2023: A paper from my group is accepted for publication in IEEE ISCAS 2023:
P. Katti, N. Skatchkovsky, O. Simeone, B. Rajendran, B. M. Al-Hashimi, Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticity.
11/2022: A paper from my group (collaborative work led by Osvaldo Simeone) is published in IEEE Transactions on Computers:
B. Rosenfeld, O. Simeone, and B. Rajendran, Spiking Generative Adversarial Networks With a Neural Network Discriminator: Local Training, Bayesian Models, and Continual Meta-Learning.
10/2022: A paper from my group (collaborative work with Jae-sun, ASU) is accepted for publication at ICEE 2022:
S. Kulkarni, S. Yin, J-S. Seo, and B. Rajendran, Neuromorphic Accelerator for Deep Spiking Neural Networks With NVM Crossbar Arrays.
09/2022: A position paper from our group with collaborators from the University of Luxembourg is accepted at the 39th International Communications Satellite Systems Conference (ICSSC):
F. Ortiz, E. Lagunas, W. Martins, T. Dinh, N. Skatchkovsky, O. Simeone, B. Rajendran, T. Navarro, S. Chatzinotas, Towards the Application of Neuromorphic Computing to Satellite Communications.
08/2022: A paper from my group (collaborative work with Saurabh Lodha) is published in Device Research Conference:
K. Thakar, B. Rajendran, and S. Lodha, Biomimetic Spiking Neuron Enabled by Subthreshold Operation of 2D Material-Based Transistor with 500 Picojoules/Spike.
02/2021: A paper from my group (collaborative work led by Osvaldo Simeone) is accepted for publication at IEEE Data Science and Learning Workshop (DSLW 2021):
B. Rosenfeld, O. Simeone, and B. Rajendran, Fast On-Device Adaptation for Spiking Neural Networks via Online-Within-Online Meta-Learning.
01/2021: A paper from my group (collaborative work with Jae-sun, ASU) is accepted for publication at ISCAS 2021:
V. Joshi, W. He, J-S. Seo, and B. Rajendran, Hybrid In-memory Computing Architecture for the Training of Deep Neural Networks.
08/2020: A paper I co-authored is published in Advanced Intelligent Systems:
Adnan Mehonic, Abu Sebastian, Bipin Rajendran, Osvaldo Simeone, Eleni Vasilaki, Anthony J. Kenyon, Memristors - From In‐Memory Computing, Deep Learning Acceleration, and Spiking Neural Networks to the Future of Neuromorphic and Bio‐Inspired Computing
06/2020: A book I co-edited with Sabina Spiga, Abu Sebastian, and Damien Querlioz is published by Elsevier:
Memristive Devices for Brain-Inspired Computing
05/2020: A paper from our group is published in Nature Communications:
V. Joshi, M. Le Gallo, S. Haefeli, I. Boybat, S. R. Nandakumar, C. Piveteau, M. Dazzi, B. Rajendran, A. Sebastian, and E. Eleftheriou, Accurate deep neural network inference using computational phase-change memory, Nature Communications, 11, Article number: 2473 (2020).
05/2020: A paper from our group is published in Scientific Reports :
S. R. Nandakumar, I. Boybat, M. Le Gallo, E. Eleftheriou, A. Sebastian and B. Rajendran, Experimental Demonstration of Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses.
03/2020: A paper from our group is published in Frontiers in Neuroscience:
S. R. Nandakumar, M. Le Gallo, C. Piveteau, V. Joshi, G. Mariani, I. Boybat, G. Karunaratne, R. Khaddam-Aljameh, U. Egger, A. Petropoulos, T. A. Antonakopoulos, B. Rajendran, A. Sebastian and E. Eleftheriou, Mixed-precision deep learning based on computational memory.
03/2020: A paper from our group is published in Microelectronic Engineering:
S. R. Nandakumar and B. Rajendran, Bio-mimetic Synaptic Plasticity and Learning in a sub-500mV Cu/SiO2/W Memristor.
01/2020: A paper from our group is accepted at ISCAS 2020:
V. Joshi, G. Karunaratne, M. Le Gallo, I. Boybat, C. Piveteau, A. Sebastian, B. Rajendran, E. Eleftheriou, ESSOP: Efficient and Scalable Stochastic Outer Product Architecture for Deep Learning, ISCAS 2020.
12/2019: A paper I co-authored is published in the IEEE Transactions on Electron Devices:
X. Xu, B. Rajendran, M. P. Anantram, Kinetic Monte Carlo Simulation of Interface-Controlled Hafnia-Based Resistive Memory
11/2019: A paper I co-authored is published in the IEEE Signal Processing Magazine:
Bipin Rajendran, Abu Sebastian, Michael Schmuker, Narayan Srinivasa, Evangelos Eleftheriou, Low-Power Neuromorphic Hardware for Signal Processing Applications: A review of architectural and system-level design approaches.
11/2019: A paper I co-authored with my previous Masters student at IIT Bombay is published in Elsevier Neurocomputing:
N. Anwani and B. Rajendran, Training Multi-layer Spiking Neural Networks using NormAD based Spatio-Temporal Error Backpropagation.
11/2019: A special issue on Brain-Inspired Computing, from Algorithmic, Hardware, and Neuroscience Perspectives that I co-edited with Osvaldo Simeone, Andre Grüning, Evangelos Eleftheriou, Mike Davies, Sophie Deneve, and Guang-Bin Huang is published in the IEEE Signal Processing Magazine.
11/2019: Dr. Rajendran gave an invited talk at Asilomar Conference on Signals, Systems, and Computers, 2019 titled "Learning with Spiking Neural Networks".
10/2019: Dr. Rajendran gave an invited talk at the IEEE Non-Volatile Memory Technology Symposium, 2019 titled "Towards Computing at the Efficiency of the Brain".
10/2019: Shruti Kulkarni successfully defends her PhD thesis.
9/2019: Two papers from our group are accepted at ICECS 2019.
S. R. Kulkarni, D. Kadetotad, S. Yin, J. Seo, and B. Rajendran, Neuromorphic Hardware Accelerator for SNN Inference based on STT-RAM Crossbar Arrays
S. R. Nandakumar, I. Boybat, V. Joshi, C. Piveteau, M. Le Gallo, B. Rajendran, A. Sebastian, and E. Eleftheriou, Phase-Change Memory Models for Deep Learning Training and Inference.
8/2019: Dr. Rajendran is selected a senior member of the US National Academy of Inventors.
05/2019: Dr. Rajendran gave an invited talk at the 11th International Memory Workshop (IMW) titled "Building Next-generation AI systems: Co-optimization of Algorithms, Architectures, and Nanoscale Memristive Devices".
05/2019: A paper from our group is accepted at SPAWC 2019:
B. Rosenfeld, O. Simeone, B. Rajendran, Learning First-to-Spike Policies for Neuromorphic Control Using Policy Gradients.
4/2019: Dr. Rajendran receives an IBM Faculty Award.
4/2019: PhD student S. R. Nandakumar selected for the 2019 NCE Outstanding Graduate Student Award and the 2019 Hashimoto Prize for Best Doctoral Dissertation in ECE Department.
2/2019: S. R. Nandakumar successfully defends his PhD thesis. He will be joining IBM Research Zurich as a post-doctoral researcher.
1/2019: Along with Prof. Keshab Parhi, Prof. Naresh Shanbhag, Prof. Bo Yuan, and Dr. Abu Sebastian, Dr. Rajendran will present a full-day tutorial at ISCAS 2019:
Energy-Efficient AI: System Architectures and Computational Models based on CMOS and Beyond-CMOS Devices.
11/2018: Dr. Rajendran gave a talk at the Workshop on Nanotechnology-Enabled Beyond-von-Neumann Computing at Army Research Laboratory, 2018:
Bio-inspired Algorithms and Nanoscale In-memory Computing Architectures for Information Processing.
10/2018: A paper from our group (in collaboration with IBM Zurich and EPFL) is presented at the Non-Volatile Memory Technology Symposium, 2018:
I. Boybat, S. R. Nandakumar, M. Le Gallo, B. Rajendran, Y. Leblebici, A. Sebastian, E. Eleftheriou, Impact of conductance drift on multi-PCM synaptic architectures.
10/2018: A paper from our group (in collaboration with IBM Zurich and EPFL) is accepted in the Journal of Applied Physics:
S. R. Nandakumar, M. Le Gallo, I. Boybat, B. Rajendran, A. Sebastian, and E. Eleftheriou, A phase-change memory model for neuromorphic computing.
09/2018: A paper from our group (in collaboration with Prof. Udayan Ganguly's group at IIT Bombay) is accepted in Elsevier Neurocomputing:
Anakha V. Babu, Sandeep lashkare, Udayan Ganguly and Bipin Rajendran, Stochastic Learning in Deep Neural Networks Based on Nanoscale PCMO Device Characteristics.
08/2018: A review article from our group is published in the IEEE Nanotechnology Magazine:
S.R. Nandakumar, Shruti R. Kulkarni, Anakha V. Babu and Bipin Rajendran, Building Brain-Inspired Computing Systems: Examining the Role of Nanoscale Devices.
07/2018: A paper from our group (in collaboration with IBM Zurich and EPFL) is accepted at EPCOS 2018:
I. Boybat, M. Le Gallo, S. R. Nandakumar, B. Rajendran, Y. Leblebici, A. Sebastian, and E. Eleftheriou, Multi-PCM synapses for spiking neural networks.
07/2018: A paper from our group, in collaboration with Dr. Jae-sun Seo's group at ASU, is accepted at SISPAD 2018:
S. R. Kulkarni, D. V. Kadetotad, J. Seo and B. Rajendran, Well-Posed Verilog-A Compact Model for Phase Change Memory.
06/2018: A paper from our group (in collaboration with IBM Zurich and EPFL) appears in Nature Communications, 2018:
I. Boybat, M. Le Gallo, S. R. Nandakumar, T. Moraitis, T. Tuma, B. Rajendran, Y. Leblebici, A. Sebastian, and E. Eleftheriou, Neuromorphic computing with multi-memristive synapses. For more information check this and this.
06/2018: A paper from our group is accepted at EANN 2018:
S. R. Kulkarni, A. V. Babu and B. Rajendran, Acceleration of Convolutional Networks using Nanoscale Memristive Devices.
05/2018: A paper from our group is accepted at SPAWC 2018:
A. Bagheri, O. Simeone, B. Rajendran, Adversarial Training for Probabilistic Spiking Neural Networks.
04/2018: Along with Dr. Abu Sebastian, Dr. Duygu Kuzum, and Dr. Manan Suri, I am organizing the MRS Spring Symposium session on Materials, Devices, and Systems for Machine Learning and Neuromorphic Computing, April 3-5, 2018.
04/2018: A paper from our group is accepted at Elsevier Neural Networks (pdf):
S. R. Kulkarni and B. Rajendran, Spiking Neural Networks for Handwritten Digit Recognition - Supervised Learning and Network Optimization.
03/2018: I gave an invited talk at the EITN Workshop ("From Neuroscience to Machine Learning") organized by Andre Gruning and European Institute for Theoretical Neuroscience, on March 12-13 in Paris, France.
02/2018: A paper from our group is accepted at ICASSP 2018:
A. Bagheri, O. Simeone, B. Rajendran, Training Probabilistic Spiking Neural Networks With First-to-Spike Decoding.
02/2018: Two papers from our group are accepted at ISCAS 2018
S. R. Kulkarni, J. M. Alexaides, B. Rajendran, Live Demonstration: Image Classification Using Bio-inspired Spiking Neural Networks.
S. R. Nandakumar, M. Le Gallo, I. Boybat, B. Rajendran, A. Sebastian, and E. Eleftheriou, Mixed-precision architecture based on computational memory for training deep neural networks.
09/2017: I will give an invited talk at the 3rd HALO Workshop (Hardware and Algorithms for Learning On-a-Chip, ) co-located at 2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).
09/2017: Two papers from our group are accepted at ICECS 2017
A. V. Babu and B. Rajendran, Stochastic Deep Learning in Memristive Networks
S. R. Kulkarni, J. M. Alexaides, B. Rajendran, Learning and Real-time Classification of Hand-written Digits With Spiking Neural Networks
09/2017: I received a competitive Faculty Seed Grant from New Jersey Institute of Technology for developing Brain-inspired Visual Learning Systems.
09/2017: A research poster from IBM Zurich, EPFL, and NJIT (with Ph.D. student S. R. Nandakumar) was adjudged among the top three at the 17th Non-Volatile Memory Technology Symposium, 2017.
06/2017: I was awarded a research grant from the US National Science Foundation on Probabilistic Learning for Deep Spiking Neural Networks.
06/2017: I will give an invited talk at the IEEE 60th International Midwest Symposium on Circuits and Systems titled "Spiking Neural Networks - Algorithms, Hardware Implementations and Applications", in Boston, MA.
06/2017: At the 75th Device Research Conference, I co-organized the following
A rump session titled “Neuromorphic computing - Do devices matter?" (with Dr. Rashmi Jha, University of Cincinnati).
A short course titled “Memory Devices for the Next 10 Years" (with Dr. Davood Shahrjerdi, NYU).
05/2017: I gave an invited talk at the 231st ECS Meeting titled "Synaptic Plasticity in a Memristive Device below 500mV", in New Orleans, LA.
05/2017: With Dr. Jae-sun Seo at ASU, I co-organized and presented a tutorial titled “Towards the Ultimate Brain Computer – Hardware Designs of Artificial & Spiking Neural Networks", at 2017 International Joint Conference on Neural Networks (IJCNN 2017) in Anchorage, AK.
03/2017: Our paper is accepted at DRC 2017:
S. R. Nandakumar, I. Boybat, M. Le Gallo, A. Sebastian, B. Rajendran, and E. Eleftheriou, Supervised Learning in Spiking Neural Networks with MLC PCM Synapses.
03/2017: Ph.D. student S. R. Nandakumar wins IBM Ph.D. Fellowship, 2017. Congratulations!
10/2016: I was awarded an SRC research grant (with Prof. Jae-sun Seo, ASU) to work on Neuromorphic Computing System Design based on Emerging Memories.
10/2016: I gave an invited talk at The IEEE Non-Volatile Memory Technology Symposium, 2016.
09/2016: I will serve on the TPC of DRC & NVMW 2017.
08/2016: Our paper is accepted at NIPS 2016 (Acceptance ratio: 0.227):
P. Tandon, Y. Malviya and B. Rajendran, Efficient and Robust Spiking Neural Circuit for Navigation Inspired by Echolocating Bats
06/2016: Our paper is accepted at SISPAD 2016:
S. R. Nandakumar and B. Rajendran, Verilog-A Compact Model for a Novel Cu/SiO2/W Quantum Memristor.
03/2016: Our paper is accepted at DRC 2016:
S. R. Nandakumar and B. Rajendran, Physics-based Switching Model for Cu/SiO2/W Quantum Memristor.
03/2016: Our paper is accepted in Nanoletters
S. R. Nandakumar, M. Minvielle, S. Nagar, C. Dubourdieu, and B. Rajendran, A 250 mV Cu/SiO2/W memristor with half-integer quantum conductance states.
01/2016: I am joining NJIT as an Associate Professor of Electrical and Computer Engineering.
Previous news, from IIT Bombay days:
Our paper is accepted at EANN 2015
S. R. Kulkarni and B. Rajendran - Scalable Digital CMOS Architecture for Spike based Supervised Learning.
Four papers from our group are accepted at IJCNN 2015
N. Anwani and B. Rajendran - Normalized Approximate Descent based Supervised Learning Rule for Spiking Neurons
S. Santurkar and B. Rajendran - C. elegans chemotaxis inspired neuromorphic circuit for contour tracking and obstacle avoidance
S. Thorat and B. Rajendran - Arithmetic Computing via Rate Coding in Neural Circuits with Spike-triggered Adaptive Synapses
C. P. Narisetty, K. Saboo and B. Rajendran - Composer Classification based on Temporal Coding in Adaptive Spiking Neural Networks
Our paper on live demonstration is accepted at ISCAS 2015.
C. Shetty, P. Shah, S. Nitchith, R. Rawat, Nandakumar S. R, S. Kulkarni & B. Rajendran - Spiking Neural Circuit Based Navigation Inspired by C. elegans Thermotaxis
My students Yogesh Singh, Vinay Joshi and Praveen Rathe won the first prize at the Ideathon Competition at VLSI Design Conference 2015.
Two manuscripts uploaded in ArXiv.
S. Santurkar & B. Rajendran - A neural circuit for navigation inspired by C. elegans Chemotaxis (Link). This work has been cited by MIT Tech Review.
S. Santurkar & B. Rajendran - Sub-threshold CMOS Spiking Neuron Circuit Design for Navigation Inspired by C. elegans Chemotaxis (Link)
Our paper with my collaborator at Georgia Tech is published in HPCA 2015.
P. J. Nair, C. Chou, B. Rajendran & M. K. Qureshi - Reducing Read Latency of Phase Change Memory via Early Read and Turbo Read
Our paper with my collaborator is published in Nature Scientific Reports.
S. Mandal, A. El-Amin, K. Alexander, B. Rajendran & R. Jha - Novel synaptic memory device for neuromorphic computing, Nat. Sci. Rep. 4, 5333; (2014).
Two papers from our group are accepted at DRC 2014
N. Panwar, D. Kumar, N. K. Upadhyay, P. Arya, U. Ganguly and B. Rajendran - Memristive Synaptic Plasticity in PCMO RRAM by Bio-mimetic Programming
R. Meshram, B. Rajendran and U. Ganguly - Biomimetic 4F2 synapse with intrinsic timescale for pulse based STDP by I-NPN selection device
Two papers from our group are accepted at IJCNN 2014
A. Bora, A. Rao and B. Rajendran - Mimicking the worm - an adaptive spiking neural circuit for contour tracking inspired by C. Elegans thermotaxis.
A. Singha, B. Muralidharan and B. Rajendran - Analog Memristive Time Dependent Learning Using Discrete Nanoscale RRAM Devices.
Our paper on a teaching-learning study conducted in a class I taught last semester is accepted at T4E, 2014.
A. Anand, A. Kothiyal, B. Rajendran & S. Murthy - Guided Problem Solving and Group Programming - A Technology-Enhanced Teaching-Learning Strategy for Engineering Problem Solving, IEEE International Conference on Technology for Education, 2014.
Paper based on a teaching-learning study conducted in Neuromorphic Engineering class I taught last year is accepted at LaTiCE, 2015.
A. Kothiyal, B. Rajendran & S. Murthy - Delayed Guidance: A teaching-learning strategy to develop ill-structured problem solving skills in engineering, International Conference on Learning and Teaching in Computing and Engineering, 2015.