| Death anxiety in hospitalized end-of-life patients as captured from a structured electronic health record: Differences by patient and nurse characteristics MK Lodhi, UI Cheema, J Stifter, DJ Wilkie, GM Keenan, Y Yao, R Ansari, ... Research in gerontological nursing 7 (5), 224-234, 2014 | 23 | 2014 |
| Outcomes for end-of-life patients with anticipatory grieving: Insights from practice with standardized nursing terminologies within an interoperable Internet-based electronic … J Johnson, MK Lodhi, U Cheema, J Stifter, K Dunn-Lopez, Y Yao, ... Journal of Hospice & Palliative Nursing 19 (3), 223-231, 2017 | 17 | 2017 |
| A high performance architecture for computing burrows-wheeler transform on FPGAs UI Cheema, AA Khokhar 2013 International Conference on Reconfigurable Computing and FPGAs …, 2013 | 12 | 2013 |
| Power-efficient re-gridding architecture for accelerating non-uniform fast fourier transform UI Cheema, G Nash, R Ansari, AA Khokhar 2014 24th International Conference on Field Programmable Logic and …, 2014 | 11 | 2014 |
| Power-efficient rma sar imaging using pipelined non-uniform fast fourier transform GT Nash, UI Cheema, R Ansari, AA Khokhar 2015 IEEE Radar Conference (RadarCon), 1600-1604, 2015 | 10 | 2015 |
| Power-efficient and highly scalable parallel graph sampling using fpgas U Tariq, UI Cheema, F Saeed 2017 International Conference on ReConFigurable Computing and FPGAs …, 2017 | 9 | 2017 |
| Invarch: A hardware eficient architecture for matrix inversion UI Cheema, G Nash, R Ansari, AA Khokhar 2015 33rd IEEE International Conference on Computer Design (ICCD), 180-187, 2015 | 7 | 2015 |
| Memory-optimized re-gridding architecture for non-uniform fast Fourier transform UI Cheema, G Nash, R Ansari, A Khokhar IEEE Transactions on Circuits and Systems I: Regular Papers 64 (7), 1853-1864, 2017 | 5 | 2017 |
| Efficient hardware acceleration of emerging neural networks for embedded machine learning: An industry perspective A Raha, R Sung, S Ghosh, PK Gupta, DA Mathaikutty, UI Cheema, ... Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing …, 2023 | 4 | 2023 |
| FPGA-based Hardware Accelerator for Image Reconstruction in Magnetic Resonance Imaging E Pezzotti, A Iacobucci, G Nash, U Cheema, P Vinella, R Ansari Proceedings of the 2017 ACM/SIGDA International Symposium on Field …, 2017 | 4 | 2017 |
| Output drain path facilitating flexible schedule-based deep neural network accelerator A Raha, DA Mathaikutty, UI Cheema, D Kondru US Patent App. 18/474,464, 2024 | 1 | 2024 |
| VPU-EM: An Event-based Modeling Framework to Evaluate NPU Performance and Power Efficiency at Scale C Qi, Y Wang, H Wang, Y Lu, SS Subramanian, F Cahill, C Tuohy, V Li, ... arXiv preprint arXiv:2303.10271, 2023 | 1 | 2023 |
| Medianpipes: An fpga based highly pipelined and scalable technique for median filtering UI Cheema, G Nash, R Ansari, AA Khokhar Proceedings of the 2015 ACM/SIGDA International Symposium on Field …, 2015 | 1 | 2015 |
| Memory optimized re-gridding for non-uniform fast fourier transform on fpgas UI Cheema, G Nash, R Ansari, AA Khokhar 2014 IEEE 22nd Annual International Symposium on Field-Programmable Custom …, 2014 | 1 | 2014 |
| Dynamic sparsity-based acceleration of neural networks A Raha, D Kondru, DA Mathaikutty, UI Cheema US Patent App. 18/543,356, 2024 | | 2024 |
| Accuracy-based approximation of activation functions with programmable look-up table having area budget UI Cheema, R Simofi, DA Mathaikutty, A Raha, D Kondru US Patent App. 18/534,035, 2024 | | 2024 |
| Switchable one-sided sparsity acceleration A Raha, DA Mathaikutty, D Kondru, UI Cheema, M Power, N Hanrahan US Patent App. 18/476,594, 2024 | | 2024 |
| Approximating activation functions with taylor series UI Cheema, DA Mathaikutty, A Raha, D Kondru, RJH Sung, SK Ghosh US Patent App. 18/346,992, 2023 | | 2023 |
| Scheduling computations in deep neural network based on sparsity RJH Sung, A Raha, DA Mathaikutty, UI Cheema US Patent App. 18/180,415, 2023 | | 2023 |
| Dynamic uncompression for channel-separable operation in neural network A Raha, DA Mathaikutty, RJH Sung, UI Cheema, D Kondru, SK Ghosh US Patent App. 18/184,921, 2023 | | 2023 |
