| Machine learning aided device simulation of work function fluctuation for multichannel gate-all-around silicon nanosheet MOSFETs C Akbar, Y Li, WL Sung IEEE Transactions on Electron Devices 68 (11), 5490-5497, 2021 | 31 | 2021 |
| Deep learning algorithms for the work function fluctuation of random nanosized metal grains on gate-all-around silicon nanowire MOSFETs C Akbar, Y Li, WL Sung IEEE Access 9, 73467-73481, 2021 | 22 | 2021 |
| Deep learning approach to inverse grain pattern of nanosized metal gate for multichannel gate-all-around silicon nanosheet MOSFETs C Akbar, Y Li, WL Sung IEEE Transactions on Semiconductor Manufacturing 34 (4), 513-520, 2021 | 19 | 2021 |
| Physics-prior Bayesian neural networks in semiconductor processing CH Chen, P Parashar, C Akbar, SM Fu, MY Syu, A Lin IEEE access 7, 130168-130179, 2019 | 14 | 2019 |
| Intelligent manufacturing: TCAD-assisted adaptive weighting neural networks CY Huang, SM Fu, P Parashar, CH Chen, C Akbar, AS Lin IEEE Access 6, 78402-78413, 2018 | 12 | 2018 |
| Intelligent photolithography corrections using dimensionality reductions P Parashar, C Akbar, TS Rawat, S Pratik, R Butola, SH Chen, YS Chang, ... IEEE Photonics Journal 11 (5), 1-15, 2019 | 6 | 2019 |
| Analytics-statistics mixed training and its fitness to semisupervised manufacturing P Parashar, CH Chen, C Akbar, SM Fu, TS Rawat, S Pratik, R Butola, ... PloS one 14 (8), e0220607, 2019 | 6 | 2019 |
| Transfer learning approach to analyzing the work function fluctuation of gate-all-around silicon nanofin field-effect transistors C Akbar, Y Li, WL Sung Computers and Electrical Engineering 103, 108392, 2022 | 4 | 2022 |
| Machine learning approach to predicting tunnel field-effect transistors C Akbar, N Thoti, Y Li 2021 International Symposium on VLSI Technology, Systems and Applications …, 2021 | 4 | 2021 |
| Application of long short-term memory modeling technique to predict process variation effects of stacked gate-all-around Si nanosheet complementary-field effect transistors R Butola, Y Li, SR Kola, C Akbar, MH Chuang Computers and Electrical Engineering 105, 108554, 2023 | 3 | 2023 |
| Estimating the process variation effects of stacked gate all around si nanosheet CFETs using artificial neural network modeling framework R Butola, Y Li, SR Kola, MH Chuang, C Akbar 2022 IEEE 22nd International Conference on Nanotechnology (NANO), 170-173, 2022 | 2 | 2022 |
| Device-simulation-based machine learning technique for the characteristic of line tunnel field-effect transistors C Akbar, Y Li, N Thoti IEEE Access 10, 53098-53107, 2022 | 2 | 2022 |
| Intelligent Modeling of Electrical Characteristics of Multi-Channel Gate All Around Silicon Nanosheet MOSFETs Induced by Work Function Fluctuation C Akbar, Y Li, WL Sung 2022 IEEE 22nd International Conference on Nanotechnology (NANO), 261-264, 2022 | 1 | 2022 |
| 2021 Index IEEE Transactions on Semiconductor Manufacturing Vol. 34 C Akbar, M Arai, S Arena, K Arima, L Bai, S Barai, BM Basol, A Beghi, ... IEEE Transactions on Semiconductor Manufacturing 34 (4), 2021 | 1 | 2021 |
| Secure AES OFDM with channel reciprocity exploitation through relative calibration C Akbar, H Mahmood, I Mustafa 2016 International Conference on Open Source Systems & Technologies (ICOSST …, 2016 | 1 | 2016 |
| Yield Modeling, Analysis, and Enhancement Dynamic Clustering for Wafer Map Patterns Using Self-Supervised Learning on Convolutional Autoencoders......... D. Kim and P. Kang 444 … C Akbar, Y Li, WL Sung | | |
| Optical Proximity Correction Using Transformation Transfer Learning P Parashar, C Akbar, S Pratik, R Butola, TS Rawat, SH Chen, A Lin | | |
| Multi-step ahead stock market index prices forecasting: Supervised versus Semi-supervised approaches P Parashar, S Nuannimnoi, C Akbar, R Butola, A Lin | | |
| Enabling Technologies for 5G Wireless Networks Title: Design of Near Field Communication Wearable A Ahmad, O Hasan, S Tahar, A Mohamed, HM Chandni Akbar | | |
