左兴权（教授）
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- 博士生导师 硕士生导师
- 教师英文名称：Zuo Xingquan
- 电子邮箱：zuoxq@bupt.edu.cn
- 所在单位：计算机学院（国家示范性软件学院）
- 学历：研究生毕业
- 办公地点：科研楼203室
- 性别：男
- 联系方式：010-62281833
- 学位：博士学位
- 在职信息：在职
- 毕业院校：哈尔滨工业大学
- 学科：计算机科学与技术*
- 所属院系：计算机学院（国家示范性软件学院）
- 邮编：100876
- 通讯/办公地址：北京邮电大学 科研楼 203室
- 办公室电话：010-62281833
- 邮箱：zuoxq@bupt.edu.cn
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- .Yahong Liu, Xingquan Zuo*, Guanqun Ai, et al., A construction-and-repair based method for vehicle scheduling of bus line with branch lines, Computers & Industrial Engineering, 2023, 178: 109103.
- .Guanqun Ai, Xingquan Zuo*, Gang Chen, Binglin Wu. Deep reinforcement learning based dynamic optimization of bus timetable, Applied Soft Computing, 2022, 131: 109752.
- .Yun Wang, Xingquan Zuo, Zhiqiang Wu, et al., Variable neighborhood search based multiobjective ACO-list scheduling for cloud workflows, Journal of Supercomputing, 2022, 78: 18856–18886.
- .Xing Wan, Xingquan Zuo*, Xinchao Zhao, A differential evolution algorithm combined with linear programming for solving a closed loop facility layout problem, Applied Soft Computing, 2022, 121: 108725.
- .Xing Wan, Xingquan Zuo*, Xiaodong Li, et al., A hybrid multiobjective GRASP for a multi-row facility layout problem with extra clearances, International Journal of Production Research, 2022, 60(3): 957-976.
- .Haojie Chen, Hai Huang, Xingquan Zuo, et al., Robustness enhancement of neural networks via architecture search with multi-objective evolutionary optimization, Mathematics, 2022, 10(15): 2724.
- .Haohan Liu, Xingquan Zuo, Hai Huang, et al., Saliency map-based local white-box adversarial attack against deep neural networks, CAAI International Conference on Artificial Intelligence, Beijing, China, 2022, pp. 3-14.
- .李瑶, 左兴权*, 等. 人工智能可解释性评估研究综述, 导航定位与授时, 2022, 9(6): 13-24.
- .Xingquan Zuo*, Xueqing Liu, Qingfu Zhang, et al., MOEA/D with linear programming for double row layout problem with center-islands, IEEE Transactions on Cybernetics, 2021, 51(7): 3549-3561.
- .Dan Luo, Dong Zhao, Qixue Ke, Xiaoyong You, Liang Liu, Desheng Zhang, Huadong Ma, Xingquan Zuo, Fine-grained service-level passenger flow prediction for bus transit systems based on multitask deep learning, IEEE Transactions on Intelligent Transportation Systems, 2021, 22(11): 7184-7199.