| Resistive crossbars as approximate hardware building blocks for machine learning: Opportunities and challenges I Chakraborty, M Ali, A Ankit, S Jain, S Roy, S Sridharan, A Agrawal, ... Proceedings of the IEEE 108 (12), 2276-2310, 2020 | 149 | 2020 |
| Proposal for a leaky-integrate-fire spiking neuron based on magnetoelectric switching of ferromagnets A Jaiswal, S Roy, G Srinivasan, K Roy IEEE Transactions on Electron Devices 64 (4), 1818-1824, 2017 | 100 | 2017 |
| TxSim: Modeling training of deep neural networks on resistive crossbar systems S Roy, S Sridharan, S Jain, A Raghunathan IEEE Transactions on Very Large Scale Integration (VLSI) Systems 29 (4), 730-738, 2021 | 65 | 2021 |
| Compute-in-memory technologies and architectures for deep learning workloads M Ali, S Roy, U Saxena, T Sharma, A Raghunathan, K Roy IEEE Transactions on Very Large Scale Integration (VLSI) Systems 30 (11 …, 2022 | 53 | 2022 |
| Pruning filters while training for efficiently optimizing deep learning networks S Roy, P Panda, G Srinivasan, A Raghunathan 2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020 | 49 | 2020 |
| PIM-DRAM: Accelerating machine learning workloads using processing in commodity DRAM S Roy, M Ali, A Raghunathan IEEE Journal on Emerging and Selected Topics in Circuits and Systems 11 (4 …, 2021 | 39 | 2021 |
| Spike timing dependent plasticity based enhanced self-learning for efficient pattern recognition in spiking neural networks G Srinivasan, S Roy, V Raghunathan, K Roy 2017 International Joint Conference on Neural Networks (IJCNN), 1847-1854, 2017 | 36 | 2017 |
| Gradual channel pruning while training using feature relevance scores for convolutional neural networks SA Aketi, S Roy, A Raghunathan, K Roy IEEE Access 8, 171924-171932, 2020 | 32 | 2020 |
| Spintronic neural systems K Roy, C Wang, S Roy, A Raghunathan, K Yang, A Sengupta Nature Reviews Electrical Engineering 1 (11), 714-729, 2024 | 16 | 2024 |
| Design tools for resistive crossbar based machine learning accelerators I Chakraborty, S Roy, S Sridharan, M Ali, A Ankit, S Jain, A Raghunathan 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits …, 2021 | 4 | 2021 |
| Breaking the memory wall: next-generation artificial intelligence hardware K Roy, A Kosta, T Sharma, S Negi, D Sharma, U Saxena, S Roy, ... Frontiers in Science 3, 1611658, 2025 | 2 | 2025 |
| Evaluation of STT-MRAM as a Scratchpad for Training in ML Accelerators S Roy, C Wang, A Raghunathan arXiv preprint arXiv:2308.02024, 2023 | 1 | 2023 |
| MEMORY-CENTRIC SYSTEM DESIGN TO ACCELERATE AI WORKLOADS S Roy Purdue University Graduate School, 2025 | | 2025 |
| KV-CAR: KV Cache Compression using Autoencoders and KV Reuse in Large Language Models S Roy, S Sridharan, S Selvam, A Raghunathan arXiv preprint arXiv:2512.06727, 2025 | | 2025 |
| Experts are all you need: A Composable Framework for Large Language Model Inference S Sridharan, S Roy, A Raghunathan, K Roy arXiv preprint arXiv:2511.22955, 2025 | | 2025 |
| Softprox: A Post-finetuning Methodology to Mitigate Softmax Bottlenecks in Transformer Workloads AR Aradhana Mohan Parvathy, Sourjya Roy, Soumendu Kumar Ghosh, Arnab Raha ... IEEE Transactions on Circuits and Systems for Artificial Intelligence …, 2025 | | 2025 |
| Row-by-row convolutional neural networks for Analog-AI P Narayanan, S Ambrogio, C Mackin, M Ishii, B Killeen, A Okazaki, ... | | 2025 |
| Brain Inspired Enhanced Learning Mechanism Based on Spike Timing Dependent Plasticity (STDP) for Efficient Pattern Recognition in Spiking Neural Networks S Roy, G Srinivasan, V Raghunathan | | 2016 |
Anand RaghunathanSilicon Valley Chair Professor of Electrical and Computer Engineering, Purdue UniversityVerified email at purdue.edu
