| ECG authentication hardware design with low-power signal processing and neural network optimization with low precision and structured compression SK Cherupally, S Yin, D Kadetotad, G Srivastava, C Bae, SJ Kim, J Seo IEEE transactions on biomedical circuits and systems 14 (2), 198-208, 2020 | 29 | 2020 |
| A smart hardware security engine combining entropy sources of ECG, HRV, and SRAM PUF for authentication and secret key generation SK Cherupally, S Yin, D Kadetotad, C Bae, SJ Kim, J Seo IEEE Journal of Solid-State Circuits 55 (10), 2680-2690, 2020 | 19 | 2020 |
| Modeling and optimization of SRAM-based in-memory computing hardware design J Saikia, S Yin, SK Cherupally, B Zhang, J Meng, M Seok, JS Seo 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE), 942-947, 2021 | 14 | 2021 |
| ECG authentication neural network hardware design with collective optimization of low precision and structured compression SK Cherupally, G Srivastava, S Yin, D Kadetotad, C Bae, SJ Kim, J Seo 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2019 | 10 | 2019 |
| Improving the accuracy and robustness of rram-based in-memory computing against rram hardware noise and adversarial attacks SK Cherupally, J Meng, AS Rakin, S Yin, I Yeo, S Yu, D Fan, JS Seo Semiconductor Science and Technology 37 (3), 034001, 2022 | 8 | 2022 |
| A 1.23-ghz 16-kb programmable and generic processing-in-sram accelerator in 65nm A Sridharan, S Angizi, SK Cherupally, F Zhang, JS Seo, D Fan ESSCIRC 2022-IEEE 48th European Solid State Circuits Conference (ESSCIRC …, 2022 | 7 | 2022 |
| Leveraging noise and aggressive quantization of in-memory computing for robust dnn hardware against adversarial input and weight attacks SK Cherupally, AS Rakin, S Yin, M Seok, D Fan, J Seo 2021 58th ACM/IEEE Design Automation Conference (DAC), 559-564, 2021 | 7 | 2021 |
| Improving DNN hardware accuracy by in-memory computing noise injection SK Cherupally, J Meng, AS Rakin, S Yin, M Seok, D Fan, JS Seo IEEE Design & Test 39 (4), 71-80, 2021 | 6 | 2021 |
| A 28nm 8-bit Floating-Point Tensor Core based CNN Training Processor with Dynamic Activation/Weight Sparsification SK Venkataramanaiah, J Meng, HS Suh, I Yeo, J Saikia, SK Cherupally, ... ESSCIRC 2022-IEEE 48th European Solid State Circuits Conference (ESSCIRC), 89-92, 2022 | 3 | 2022 |
| Hierarchical Random Boolean Network Reservoirs SK Cherupally | 3 | 2018 |
| A 28-nm 8-bit Floating-Point Tensor Core-Based Programmable CNN Training Processor With Dynamic Structured Sparsity SK Venkataramanaiah, J Meng, HS Suh, I Yeo, J Saikia, SK Cherupally, ... IEEE Journal of Solid-State Circuits, 2023 | 2 | 2023 |
| Smart hardware security engine using biometric features and hardware-specific features J Seo, S Yin, SK Cherupally US Patent 11,698,952, 2023 | | 2023 |
| Methods of training deep neural networks (dnn) using signal non-idealities and quantization associated with in-memory operations and related devices AS Rakin, D Fan, SK Cherupally, J Seo US Patent App. 17/931,682, 2023 | | 2023 |
| Hardware noise-aware training for improving accuracy of in-memory computing-based deep neural network hardware SK Cherupally, J Meng, S Yin, D Fan US Patent App. 17/714,677, 2022 | | 2022 |
| Machine Learning Assisted Security for Edge Computing Applications SK Cherupally Arizona State University, 2022 | | 2022 |
| A Smart Hardware Security Engine Combining Entropy Sources of ECG, HRV and SRAM PUF for Authentication and Secret Key Generation SK Cherupally, S Yin, D Kadetotad, C Bae, SJ Kim, JS Seo 2019 IEEE Asian Solid-State Circuits Conference (A-SSCC), 145-148, 2019 | | 2019 |
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