| Deepgate: Learning neural representations of logic gates M Li, S Khan, Z Shi, N Wang, H Yu, Q Xu Proceedings of the 59th ACM/IEEE Design Automation Conference, 667-672, 2022 | 33 | 2022 |
| Large circuit models: opportunities and challenges L Chen, Y Chen, Z Chu, W Fang, TY Ho, R Huang, Y Huang, S Khan, M Li, ... Science China Information Sciences 67 (10), 200402, 2024 | 23* | 2024 |
| DeepGate2: Functionality-Aware Circuit Representation Learning Z Shi, H Pan, K Sadaf, M Li, Y Liu, J Huang, HL Zhen, M Yuan, Z Chu, ... 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD), 2023 | 20 | 2023 |
| On EDA-Driven Learning for SAT Solving M Li, Z Shi, Q Lai, S Khan, S Cai, Q Xu 2023 60th ACM/IEEE Design Automation Conference (DAC), 1-6, 2023 | 19* | 2023 |
| SATformer: Transformer-Based UNSAT Core Learning Z Shi, M Li, Y Liu, S Khan, J Huang, HL Zhen, M Yuan, Q Xu 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD), 1-4, 2023 | 14* | 2023 |
| Deeptpi: Test point insertion with deep reinforcement learning Z Shi, M Li, S Khan, L Wang, N Wang, Y Huang, Q Xu 2022 IEEE International Test Conference (ITC), 194-203, 2022 | 14 | 2022 |
| Design space exploration of galois and fibonacci configuration based on espresso stream cipher Z Shi, C Chen, G Yang, H Xiong, F Li, H Hu, Z Wan ACM Transactions on Reconfigurable Technology and Systems 16 (3), 1-24, 2023 | 9 | 2023 |
| DeepSeq: Deep Sequential Circuit Learning S Khan, Z Shi, M Li, Q Xu 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1-2, 2024 | 7 | 2024 |
| Hardware optimizations of fruit-80 stream cipher: smaller than grain G Yang, Z Shi, C Chen, H Xiong, F Li, H Hu, Z Wan ACM Transactions on Reconfigurable Technology and Systems 16 (2), 1-32, 2023 | 5 | 2023 |
| Customized FPGA implementation of authenticated lightweight cipher fountain for IoT systems Z Shi, C Chen, G Yang, H Zhou, H Xiong, Z Wan ACM Transactions on Embedded Computing Systems 24 (2), 1-26, 2025 | 2 | 2025 |
| DeepGate3: towards scalable circuit representation learning Z Shi, Z Zheng, S Khan, J Zhong, M Li, Q Xu arXiv preprint arXiv:2407.11095, 2024 | 2 | 2024 |
| EDA-Driven Preprocessing for SAT Solving Z Shi, T Tang, S Khan, HL Zhen, M Yuan, Z Chu, Q Xu arXiv preprint arXiv:2403.19446, 2024 | 2 | 2024 |
| Addressing variable dependency in gnn-based SAT solving Z Yan, M Li, Z Shi, W Zhang, Y Chen, H Zhang arXiv preprint arXiv:2304.08738, 2023 | 2 | 2023 |
| Work-in-progress: Towards a smaller than grain stream cipher: optimized fpga implementations of fruit-80 G Yang, Z Shi, C Chen, H Xiong, H Hu, Z Wan, K Gai, M Qiu 2022 International Conference on Compilers, Architecture, and Synthesis for …, 2022 | 2 | 2022 |
| The Elephant in the Room: Variable Dependency in GNN-based SAT Solving Z Yan, M Li, Z Shi, W Zhang, YC Chen, H Zhang First International Workshop on Deep Learning-aided Verification, 0 | 1 | |
| DeepSeq2: Enhanced Sequential Circuit Learning with Disentangled Representations S Khan, Z Shi, Z Zheng, M Li, Q Xu arXiv preprint arXiv:2411.00530, 2024 | | 2024 |
| AsymSAT: Accelerating SAT Solving with Asymmetric Graph-Based Model Prediction Z Yan, M Li, Z Shi, W Zhang, Y Chen, H Zhang 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1-2, 2024 | | 2024 |
| Testability-Aware Low Power Controller Design with Evolutionary Learning M Li, Z Shi, Z Wang, W Zhang, Y Huang, Q Xu 2021 IEEE International Test Conference (ITC), 324-328, 2021 | | 2021 |
| DeepCircuitX: Repository-Level RTL Dataset for Code Understanding, Generation, and Multimodal Analysis Z Li, XU Changran, Z Shi, Z Peng, Y Liu, Y Zhou, L Zhou, C Ma, J Zhong, ... | | |
| CKTSAT: Circuit Preprocessing Driven SAT Solver J Zhu, Z Shi, Y Liu, Q Xu SAT COMPETITION 2024, 28, 0 | | |
Min LINoah's Ark Lab, Huawei TechnologiesVerified email at huawei.com
