| 2025 | ASPDAC | An Efficient General-Purpose Optical Accelerator for Neural Networks. | Sijie Fei, Amro Eldebiky, Grace Li Zhang, Bing Li, Ulf Schlichtmann |
| 2024 | DATE | Class-Aware Pruning for Efficient Neural Networks. | Mengnan Jiang, Jingcun Wang, Amro Eldebiky, Xunzhao Yin, Cheng Zhuo, Ing-Chao Lin, Grace Li Zhang |
| 2024 | DATE | OplixNet: Towards Area-Efficient Optical Split-Complex Networks with Real-to-Complex Data Assignment and Knowledge Distillation. | Ruidi Qiu, Amro Eldebiky, Grace Li Zhang, Xunzhao Yin, Cheng Zhuo, Ulf Schlichtmann, Bing Li |
| 2024 | ICCAD | BasisN: Reprogramming-Free RRAM-Based In-Memory-Computing by Basis Combination for Deep Neural Networks. | Amro Eldebiky, Grace Li Zhang, Xunzhao Yin, Cheng Zhuo, Ing-Chao Lin, Ulf Schlichtmann, Bing Li |
| 2023 | DATE | CorrectNet: Robustness Enhancement of Analog In-Memory Computing for Neural Networks by Error Suppression and Compensation. | Amro Eldebiky, Grace Li Zhang, Georg Bcherer, Bing Li, Ulf Schlichtmann |
| 2023 | DATE | Countering Uncertainties in In-Memory-Computing Platforms with Statistical Training, Accuracy Compensation and Recursive Test. | Amro Eldebiky, Grace Li Zhang, Bing Li |
| 2023 | ICCAD | NearUni: Near-Unitary Training for Efficient Optical Neural Networks. | Amro Eldebiky, Bing Li, Grace Li Zhang |