Guan Xiuxian

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HKU-SusTech Joint PhD student (2021Fall--Now) supervised by Prof. Cui from HKU and Prof. Wang from SusTech.

GitHub | HKU Email | SusTech Email

Welcome to Guan Xiuxian’s Personal Homepage

I am currently a HKU-SusTech Joint PhD student (2021Fall–Now) in Department of Computer Science, HKU and Department of Electrical & Electronic Engineering, SusTech. I received Bachelor’s Degree in Department of Computer Science and Technology in The University of Science and Technology of China (USTC) in 2020.

Publications

  1. Xiuxian Guan, Zekai Sun, Shengliang Deng, Xusheng Chen, Shixiong Zhao, Zongyuan Zhang, Tianyang Duan, Yuexuan Wang, Chenshu Wu, Yong Cui, Libo Zhang, Yanjun Wu, Rui Wang, Heming Cui, “ROG: A High Performance and Robust Distributed Training System for Robotic IoT,” in MICRO 2022, doi: 10.1109/MICRO56248.2022.00032.

  2. Deng Shengliang, Guan Xiuxian, Sun Zekai, Zhao Shixiong, Shen Tianxiang, Chen Xusheng, Duan Tianyang, Wang Yuexuan, Pan Jia, Wu Yanjun, Zhang Libo, Cui Heming, “COORP: Satisfying Low-Latency and High-Throughput Requirements of Wireless Network for Coordinated Robotic Learning,” in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2022.3140400.

  3. X. Guan, S. Deng, Z. Sun, S. Zhao, T. Li, T. Shen, Y. Wang, R. Wang, H. Cui, “MVSAS: Semantic-Aware Scheduling for Low Latency and High Precision in Wireless Multi-View Application,” 2021 IEEE 27th International Conference on Parallel and Distributed Systems (ICPADS), 2021, pp. 266-273, doi: 10.1109/ICPADS53394.2021.00039.

  4. S. Zhao, F. Li, X. Chen, X. Guan, J. Jiang, D. Huang, Y. Qing, S. Wang, P. Wang, G. Zhang, C. Li, P. Luo, H. Cui, “vPipe: A Virtualized Acceleration System for Achieving Efficient and Scalable Pipeline Parallel DNN Training,” in IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 3, pp. 489-506, 1 March 2022, doi: 10.1109/TPDS.2021.3094364.

  5. G. Xiuxian, L. Yawei, W. Yuexuan, S. Zekai, D. Shengliang and C. Heming, “CTDMA: Color-aware TDMA Network System For Low latency and High Throughput in Dense D2D Wireless Network,” 2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), 2020, pp. 318-328, doi: 10.1109/MASS50613.2020.00047.