Timing analysis of tree-like RLC circuits. - Bipin Rajendran; Veerbhan Kheterpal; Abhishek Das; Jayanta Majumder; Chittaranjan A. Mandal; P. P. Chakrabarti 001 (ISCAS (4), 2002)

Self-consistent power/performance/reliability analysis for copper interconnects. - Bipin Rajendran; Pawan Kapur; Krishna Saraswat; R. Fabian W. Pease (SLIP, 2004)

Coding for sensing in Content Addressable Memories. - Luis Alfonso Lastras-Montaño; Michele Franceschini; Bipin Rajendran; C. Lam (ISIT, 2010)

Phase Change Memory. - H.-S. Philip Wong; Simone Raoux; SangBum Kim; Jiale Liang; John P. Reifenberg; Bipin Rajendran; Mehdi Asheghi; Kenneth E. Goodson (Proc. IEEE, 2010)

A 45nm CMOS neuromorphic chip with a scalable architecture for learning in networks of spiking neurons. - Jae-sun Seo; Bernard Brezzo; Yong Liu 023; Benjamin D. Parker; Steven K. Esser; Robert K. Montoye; Bipin Rajendran; José A. Tierno; Leland Chang; Dharmendra S. Modha; Daniel J. Friedman (CICC, 2011)

Phase Change Memory: From Devices to Systems - Moinuddin K. Qureshi; Sudhanva Gurumurthi; Bipin Rajendran (Phase Change Memory, 2011)

Efficient scrub mechanisms for error-prone emerging memories. - Manu Awasthi; Manjunath Shevgoor; Kshitij Sudan; Bipin Rajendran; Rajeev Balasubramonian; Viji Srinivasan (HPCA, 2012)

Pulsed laser annealing: A scalable and practical technology for monolithic 3D IC. - Bipin Rajendran; Albert K. Henning; Brian Cronquist; Zvi Or-Bach (3DIC, 2013)

Embedded tutorial - Can silicon machines match the efficiency of the human brain? - Bipin Rajendran (VLSI Design, 2013)

Nanoscale electronic synapses using phase change devices. - Bryan L. Jackson; Bipin Rajendran; Gregory S. Corrado; Matthew J. Breitwisch; Geoffrey W. Burr; Roger Cheek; Kailash Gopalakrishnan; Simone Raoux; Charles T. Rettner; Alvaro Padilla; Alejandro G. Schrott; Rohit S. Shenoy; et al. (ACM J. Emerg. Technol. Comput. Syst., 2013)

Mimicking the worm - An adaptive spiking neural circuit for contour tracking inspired by C. Elegans thermotaxis. - Ashish Bora; Arjun Rao; Bipin Rajendran (IJCNN, 2014)

Analog memristive time dependent learning using discrete nanoscale RRAM devices. - Aniket Singha; Bhaskaran Muralidharan; Bipin Rajendran (IJCNN, 2014)

Guided Problem Solving and Group Programming: A Technology-Enhanced Teaching-Learning Strategy for Engineering Problem Solving. - Abhinav Anand; Aditi Kothiyal; Bipin Rajendran; Sahana Murthy (T4E, 2014)

A neural circuit for navigation inspired by C. elegans Chemotaxis. - Shibani Santurkar; Bipin Rajendran (CoRR, 2014)

Sub-threshold CMOS Spiking Neuron Circuit Design for Navigation Inspired by C. elegans Chemotaxis. - Shibani Santurkar; Bipin Rajendran (CoRR, 2014)

Scalable Digital CMOS Architecture for Spike Based Supervised Learning. - Shruti R. Kulkarni; Bipin Rajendran (EANN, 2015)

Reducing read latency of phase change memory via early read and Turbo Read. - Prashant J. Nair; Chia-Chen Chou; Bipin Rajendran; Moinuddin K. Qureshi (HPCA, 2015)

Increasing reconfigurability with memristive interconnects. - John Demme; Bipin Rajendran; Steven M. Nowick; Simha Sethumadhavan (ICCD, 2015)

NormAD - Normalized Approximate Descent based supervised learning rule for spiking neurons. - Navin Anwani; Bipin Rajendran (IJCNN, 2015)

Composer classification based on temporal coding in adaptive spiking neural networks. - Chaitanya Prasad N; Krishnakant V. Saboo; Bipin Rajendran (IJCNN, 2015)

C. elegans chemotaxis inspired neuromorphic circuit for contour tracking and obstacle avoidance. - Shibani Santurkar; Bipin Rajendran (IJCNN, 2015)

Arithmetic computing via rate coding in neural circuits with spike-triggered adaptive synapses. - Sushrut Thorat; Bipin Rajendran (IJCNN, 2015)

Live demonstration: Spiking neural circuit based navigation inspired by C. elegans thermotaxis. - Chirag Shetty; Sri Nitchith; Rishabh Rawat; S. R. Nandakumar; Pritesh Shah; Shruti R. Kulkarni; Bipin Rajendran (ISCAS, 2015)

Delayed Guidance: A Teaching-Learning Strategy to Develop Ill-Structured Problem Solving Skills in Engineering. - Aditi Kothiyal; Bipin Rajendran; Sahana Murthy (LaTiCE, 2015)

Tutorial T1: Neuromorphic Computing - Algorithms, Devices and Systems. - Bipin Rajendran; Udaya S. Ganguly; Manan Suri (VLSID, 2015)

Efficient and Robust Spiking Neural Circuit for Navigation Inspired by Echolocating Bats. - Bipin Rajendran; Pulkit Tandon; Yash H. Malviya (NIPS, 2016)

Neuromorphic Computing Based on Emerging Memory Technologies. - Bipin Rajendran; Fabien Alibart (IEEE J. Emerg. Sel. Topics Circuits Syst., 2016)

Stochastic deep learning in memristive networks. - Anakha V. Babu; Bipin Rajendran (ICECS, 2017)

Learning and real-time classification of hand-written digits with spiking neural networks. - Shruti R. Kulkarni; John M. Alexiades; Bipin Rajendran (ICECS, 2017)

Spiking neural networks - Algorithms, hardware implementations and applications. - Shruti R. Kulkarni; Anakha V. Babu; Bipin Rajendran (MWSCAS, 2017)

An efficient synaptic architecture for artificial neural networks. - Irem Boybat; Manuel Le Gallo; S. R. Nandakumar; Timoleon Moraitis; Tomas Tuma; Bipin Rajendran; Yusuf Leblebici; Abu Sebastian; Evangelos Eleftheriou (NVMTS, 2017)

Neuromorphic computing with multi-memristive synapses. - Irem Boybat; Manuel Le Gallo; S. R. Nandakumar; Timoleon Moraitis; Thomas P. Parnell; Tomas Tuma; Bipin Rajendran; Yusuf Leblebici; Abu Sebastian; Evangelos Eleftheriou (CoRR, 2017)

Mixed-precision training of deep neural networks using computational memory. - S. R. Nandakumar; Manuel Le Gallo; Irem Boybat; Bipin Rajendran; Abu Sebastian; Evangelos Eleftheriou (CoRR, 2017)

Acceleration of Convolutional Networks Using Nanoscale Memristive Devices. - Shruti R. Kulkarni; Anakha V. Babu; Bipin Rajendran (EANN, 2018)

Training Probabilistic Spiking Neural Networks with First- To-Spike Decoding. - Alireza Bagheri; Osvaldo Simeone; Bipin Rajendran (ICASSP, 2018)

Live Demonstration: Image Classification Using Bio-inspired Spiking Neural Networks. - Shruti R. Kulkarni; John M. Alexiades; Bipin Rajendran (ISCAS, 2018)

Mixed-precision architecture based on computational memory for training deep neural networks. - S. R. Nandakumar; Manuel Le Gallo; Irem Boybat; Bipin Rajendran; Abu Sebastian; Evangelos Eleftheriou (ISCAS, 2018)

Impact of conductance drift on multi-PCM synaptic architectures. - Irem Boybat; S. R. Nandakumar; Manuel Le Gallo; Bipin Rajendran; Yusuf Leblebici; Abu Sebastian; Evangelos Eleftheriou (NVMTS, 2018)

Adversarial Training for Probabilistic Spiking Neural Networks. - Alireza Bagheri; Osvaldo Simeone; Bipin Rajendran (SPAWC, 2018)

Training Multilayer Spiking Neural Networks using NormAD based Spatio-Temporal Error Backpropagation. - Navin Anwani; Bipin Rajendran (CoRR, 2018)

Stochastic learning in deep neural networks based on nanoscale PCMO device characteristics. - Anakha V. Babu; Sandip Lashkare; Udayan Ganguly; Bipin Rajendran (Neurocomputing, 2018)

Spiking neural networks for handwritten digit recognition - Supervised learning and network optimization. - Shruti R. Kulkarni; Bipin Rajendran (Neural Networks, 2018)

Neuromorphic Hardware Accelerator for SNN Inference based on STT-RAM Crossbar Arrays. - Shruti R. Kulkarni; Deepak Vinayak Kadetotad; Shihui Yin; Jae-Sun Seo; Bipin Rajendran (ICECS, 2019)

Phase-Change Memory Models for Deep Learning Training and Inference. - S. R. Nandakumar; Irem Boybat; Vinay Joshi; Christophe Piveteau; Manuel Le Gallo; Bipin Rajendran; Abu Sebastian; Evangelos Eleftheriou (ICECS, 2019)

Learning First-to-Spike Policies for Neuromorphic Control Using Policy Gradients. - Bleema Rosenfeld; Osvaldo Simeone; Bipin Rajendran (SPAWC, 2019)

Computational memory-based inference and training of deep neural networks. - Abu Sebastian; Irem Boybat; Martino Dazzi; Iason Giannopoulos; Vara Prasad Jonnalagadda; Vinay Joshi; Geethan Karunaratne; Benedikt Kersting; Riduan Khaddam-Aljameh; S. R. Nandakumar; Anastasios Petropoulos; Christophe Piveteau; et al. (VLSI Circuits, 2019)

Low-Power Neuromorphic Hardware for Signal Processing Applications. - Bipin Rajendran; Abu Sebastian; Michael Schmuker; Narayan Srinivasa; Evangelos Eleftheriou (CoRR, 2019)

Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses. - S. R. Nandakumar; Irem Boybat; Manuel Le Gallo; Evangelos Eleftheriou; Abu Sebastian; Bipin Rajendran (CoRR, 2019)

Accurate deep neural network inference using computational phase-change memory. - Vinay Joshi; Manuel Le Gallo; Irem Boybat; Simon Haefeli; Christophe Piveteau; Martino Dazzi; Bipin Rajendran; Abu Sebastian; Evangelos Eleftheriou (CoRR, 2019)

Low-Power Neuromorphic Hardware for Signal Processing Applications: A review of architectural and system-level design approaches. - Bipin Rajendran; Abu Sebastian; Michael Schmuker; Narayan Srinivasa; Evangelos Eleftheriou (IEEE Signal Process. Mag., 2019)

Learning Algorithms and Signal Processing for Brain-Inspired Computing [From the Guest Editors]. - Osvaldo Simeone; Bipin Rajendran; André Grüning; Evangelos Eleftheriou; Mike Davies 002; Sophie Denève; Guang-Bin Huang (IEEE Signal Process. Mag., 2019)

An On-Chip Learning Accelerator for Spiking Neural Networks using STT-RAM Crossbar Arrays. - Shruti R. Kulkarni; Shihui Yin; Jae-sun Seo; Bipin Rajendran (DATE, 2020)

ESSOP: Efficient and Scalable Stochastic Outer Product Architecture for Deep Learning. - Vinay Joshi; Geethan Karunaratne; Manuel Le Gallo; Irem Boybat; Christophe Piveteau; Abu Sebastian; Bipin Rajendran; Evangelos Eleftheriou (ISCAS, 2020)

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; Anthony J. Kenyon (Adv. Intell. Syst., 2020)

Bio-mimetic Synaptic Plasticity and Learning in a sub-500mV Cu/SiO2/W Memristor. - S. R. Nandakumar; Bipin Rajendran (CoRR, 2020)

Mixed-precision deep learning based on computational memory. - S. R. Nandakumar; Manuel Le Gallo; Christophe Piveteau; Vinay Joshi; Giovanni Mariani; Irem Boybat; Geethan Karunaratne; Riduan Khaddam-Aljameh; Urs Egger; Anastasios Petropoulos; Theodore Antonakopoulos 001; Bipin Rajendran; et al. (CoRR, 2020)

Memristors - from In-memory computing, Deep Learning Acceleration, Spiking Neural Networks, to the Future of Neuromorphic and Bio-inspired Computing. - Adnan Mehonic; Abu Sebastian; Bipin Rajendran; Osvaldo Simeone; Eleni Vasilaki; Anthony J. Kenyon (CoRR, 2020)

SpinAPS: A High-Performance Spintronic Accelerator for Probabilistic Spiking Neural Networks. - Anakha V. Babu; Osvaldo Simeone; Bipin Rajendran (CoRR, 2020)

Training multi-layer spiking neural networks using NormAD based spatio-temporal error backpropagation. - Navin Anwani; Bipin Rajendran (Neurocomputing, 2020)

Hybrid In-Memory Computing Architecture for the Training of Deep Neural Networks. - Vinay Joshi; Wangxin He; Jae-sun Seo; Bipin Rajendran (ISCAS, 2021)

Fast On-Device Adaptation for Spiking Neural Networks via Online-Within-Online Meta-Learning. - Bleema Rosenfeld; Bipin Rajendran; Osvaldo Simeone (CoRR, 2021)

Spiking Generative Adversarial Networks With a Neural Network Discriminator: Local Training, Bayesian Models, and Continual Meta-Learning. - Bleema Rosenfeld; Osvaldo Simeone; Bipin Rajendran (IEEE Trans. Computers, 2022)

A Convolutional Spiking Network for Gesture Recognition in Brain-Computer Interfaces. - Yiming Ai; Bipin Rajendran (AICAS, 2023)

Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticity. - Prabodh Katti; Nicolas Skatchkovsky; Osvaldo Simeone; Bipin Rajendran; Bashir M. Al-Hashimi (ISCAS, 2023)

Energy-Efficient On-Board Radio Resource Management for Satellite Communications via Neuromorphic Computing. - Flor Ortiz; Nicolas Skatchkovsky; Eva Lagunas; Wallace A. Martins; Geoffrey Eappen; Saed Daoud; Osvaldo Simeone; Bipin Rajendran; Symeon Chatzinotas (CoRR, 2023)

Towards Efficient and Trustworthy AI Through Hardware-Algorithm-Communication Co-Design. - Bipin Rajendran; Osvaldo Simeone; Bashir M. Al-Hashimi (CoRR, 2023)

Noise Adaptor in Spiking Neural Networks. - Chen Li; Bipin Rajendran (CoRR, 2023)

Stochastic Spiking Attention: Accelerating Attention with Stochastic Computing in Spiking Networks. - Zihang Song; Prabodh Katti; Osvaldo Simeone; Bipin Rajendran (AICAS, 2024)

Welcome Message from the Chairs. - Amit Singh; Payam Barnaghi; Geoff V. Merrett; Eiman Kanjo; Rishad A. Shafik; Aurora Gil de Castro; Florenc Demrozi; Federica Zonzini; Amna Anwar; Bipin Rajendran; Osvaldo Simeone (COINS, 2024)

Baseline Drift Tolerant Signal Encoding for ECG Classification with Deep Learning. - Robert O'Shea; Prabodh Katti; Bipin Rajendran (EMBC, 2024)

Bayesian Inference Accelerator for Spiking Neural Networks. - Prabodh Katti; Anagha Nimbekar; Chen Li; Amit Acharyya; Bashir M. Al-Hashimi; Bipin Rajendran (ISCAS, 2024)

Satellite Adaptive Onboard Beamforming Using Neuromorphic Processors. - Wallace A. Martins; Eva Lagunas; Nicolas Skatchkovsky; Flor Ortiz; Geoffrey Eappen; Osvaldo Simeone; Bipin Rajendran; Symeon Chatzinotas (PIMRC, 2024)

Hardware-Software Co-optimised Fast and Accurate Deep Reconfigurable Spiking Inference Accelerator Architecture Design Methodology. - Anagha Nimbekar; Prabodh Katti; Chen Li; Bashir M. Al-Hashimi; Amit Acharyya; Bipin Rajendran (SOCC, 2024)

Neuromorphic In-Context Learning for Energy-Efficient MIMO Symbol Detection. - Zihang Song; Osvaldo Simeone; Bipin Rajendran (SPAWC, 2024)

Baseline Drift Tolerant Signal Encoding for ECG Classification with Deep Learning. - Robert O. Shea; Prabodh Katti; Bipin Rajendran (CoRR, 2024)

Neuromorphic Wireless Split Computing with Multi-Level Spikes. - Dengyu Wu; Jiechen Chen; Bipin Rajendran; H. Vincent Poor; Osvaldo Simeone (CoRR, 2024)

Bayes2IMC: In-Memory Computing for Bayesian Binary Neural Networks. - Prabodh Katti; Clement Ruah; Osvaldo Simeone; Bashir M. Al-Hashimi; Bipin Rajendran (CoRR, 2024)

Efficient Deployment of Transformer Models in Analog In-Memory Computing Hardware. - Chen Li; Corey Lammie; Manuel Le Gallo; Bipin Rajendran (CoRR, 2024)

Noise Adaptor: Enhancing Low-Latency Spiking Neural Networks through Noise-Injected Low-Bit ANN Conversion. - Chen Li; Bipin Rajendran (CoRR, 2024)

Performance Evaluation of Neuromorphic Hardware for Onboard Satellite Communication Applications. - Eva Lagunas; Flor G. Ortiz-Gomez; Geoffrey Eappen; Saed Daoud; Wallace A. Martins; Jorge Querol; Symeon Chatzinotas; Nicolas Skatchkovsky; Bipin Rajendran; Osvaldo Simeone (IEEE Wirel. Commun., 2024)

Sparsity-Aware Optimization of In-Memory Bayesian Binary Neural Network Accelerators. - Prabodh Katti; Bashir M. Al-Hashimi; Bipin Rajendran (ISCAS, 2025)

Closed-Form Feedback-Free Learning with Forward Projection. - Robert O'Shea; Bipin Rajendran (CoRR, 2025)

Turbo-ICL: In-Context Learning-Based Turbo Equalization. - Zihang Song; Matteo Zecchin; Bipin Rajendran; Osvaldo Simeone (CoRR, 2025)

Neuromorphic Wireless Split Computing with Resonate-and-Fire Neurons. - Dengyu Wu; Jiechen Chen; H. Vincent Poor; Bipin Rajendran; Osvaldo Simeone (CoRR, 2025)

Stochastic Quantum Spiking Neural Networks with Quantum Memory and Local Learning. - Jiechen Chen; Bipin Rajendran; Osvaldo Simeone (CoRR, 2025)

Xpikeformer: Hybrid Analog-Digital Hardware Acceleration for Spiking Transformers. - Zihang Song; Prabodh Katti; Osvaldo Simeone; Bipin Rajendran (IEEE Trans. Very Large Scale Integr. Syst., 2025)