| Nanoscale hafnium oxide rram devices exhibit pulse dependent behavior and multi-level resistance capability K Beckmann, J Holt, H Manem, J Van Nostrand, NC Cady Mrs Advances 1 (49), 3355-3360, 2016 | 86 | 2016 |
| A practical hafnium-oxide memristor model suitable for circuit design and simulation S Amer, S Sayyaparaju, GS Rose, K Beckmann, NC Cady 2017 IEEE International Symposium on Circuits and Systems (ISCAS), 1-4, 2017 | 65 | 2017 |
| Pulse width and height modulation for multi-level resistance in bi-layer TaOx based RRAM Z Alamgir, K Beckmann, J Holt, NC Cady Applied Physics Letters 111 (6), 2017 | 43 | 2017 |
| Techniques for improved reliability in memristive crossbar PUF circuits M Uddin, MB Majumder, GS Rose, K Beckmann, H Manem, Z Alamgir, ... 2016 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 212-217, 2016 | 43 | 2016 |
| Accurate inference with inaccurate RRAM devices: Statistical data, model transfer, and on-line adaptation G Charan, J Hazra, K Beckmann, X Du, G Krishnan, RV Joshi, NC Cady, ... 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020 | 41 | 2020 |
| Performance enhancement of a time-delay PUF design by utilizing integrated nanoscale ReRAM devices K Beckmann, H Manem, NC Cady IEEE Transactions on Emerging Topics in Computing 5 (3), 304-316, 2016 | 37 | 2016 |
| Flow-based computing on nanoscale crossbars: Design and implementation of full adders Z Alamgir, K Beckmann, N Cady, A Velasquez, SK Jha 2016 IEEE International Symposium on Circuits and Systems (ISCAS), 1870-1873, 2016 | 37 | 2016 |
| Design considerations for memristive crossbar physical unclonable functions M Uddin, MDB Majumder, K Beckmann, H Manem, Z Alamgir, NC Cady, ... ACM Journal on Emerging Technologies in Computing Systems (JETC) 14 (1), 1-23, 2017 | 29 | 2017 |
| Towards synaptic behavior of nanoscale reram devices for neuromorphic computing applications K Beckmann, W Olin-Ammentorp, G Chakma, S Amer, GS Rose, C Hobbs, ... ACM Journal on Emerging Technologies in Computing Systems (JETC) 16 (2), 1-18, 2020 | 23 | 2020 |
| Silicon-CMOS compatible in-situ CCVD grown graphene transistors with ultra-high on/off-current ratio PJ Wessely, F Wessely, E Birinci, K Beckmann, B Riedinger, U Schwalke Physica E: Low-dimensional Systems and Nanostructures 44 (7-8), 1132-1135, 2012 | 22 | 2012 |
| Improving the Memory Window/Resistance Variability Trade-Off for 65nm CMOS Integrated HfO2 Based Nanoscale RRAM Devices J Hazra, M Liehr, K Beckmann, S Rafiq, N Cady 2019 IEEE International Integrated Reliability Workshop (IIRW), 1-4, 2019 | 21 | 2019 |
| Fabrication and performance of hybrid reram-cmos circuit elements for dynamic neural networks M Liehr, J Hazra, K Beckmann, W Olin-Ammentorp, N Cady, R Weiss, ... Proceedings of the International Conference on Neuromorphic Systems, 1-4, 2019 | 19 | 2019 |
| Stochasticity and robustness in spiking neural networks W Olin-Ammentorp, K Beckmann, CD Schuman, JS Plank, NC Cady Neurocomputing 419, 23-36, 2021 | 18 | 2021 |
| Impact of switching variability of 65nm CMOS integrated hafnium dioxide-based ReRAM devices on distinct level operations M Liehr, J Hazra, K Beckmann, S Rafiq, N Cady 2020 IEEE International Integrated Reliability Workshop (IIRW), 1-4, 2020 | 18 | 2020 |
| Robust RRAM-based in-memory computing in light of model stability G Krishnan, J Sun, J Hazra, X Du, M Liehr, Z Li, K Beckmann, RV Joshi, ... 2021 IEEE International Reliability Physics Symposium (IRPS), 1-5, 2021 | 16 | 2021 |
| Material to system-level benchmarking of CMOS-integrated RRAM with ultra-fast switching for low power on-chip learning M Abedin, N Gong, K Beckmann, M Liehr, I Saraf, O Van der Straten, ... Scientific Reports 13 (1), 14963, 2023 | 15 | 2023 |
| Optimization of switching metrics for cmos integrated hfo2 based rram devices on 300 mm wafer platform J Hazra, M Liehr, K Beckmann, M Abedin, S Rafq, N Cady 2021 IEEE International Memory Workshop (IMW), 1-4, 2021 | 14 | 2021 |
| An extendable multi-purpose 3D neuromorphic fabric using nanoscale memristors H Manem, K Beckmann, M Xu, R Carroll, R Geer, NC Cady 2015 IEEE Symposium on Computational Intelligence for Security and Defense …, 2015 | 14 | 2015 |
| Exploring model stability of deep neural networks for reliable RRAM-based in-memory acceleration G Krishnan, L Yang, J Sun, J Hazra, X Du, M Liehr, Z Li, K Beckmann, ... IEEE Transactions on Computers 71 (11), 2740-2752, 2022 | 13 | 2022 |
| The effect of different oxygen exchange layers on TaOx based RRAM devices Z Alamgir, J Holt, K Beckmann, NC Cady Semiconductor Science and Technology 33 (1), 015014, 2017 | 13 | 2017 |
Nathaniel C. CadyEmpire Innovation Professor, SUNY Polytechnic InstituteVerified email at sunypoly.edu
