人物简介
余维杰,计算机应用技术专业博士,现任pg麻将胡了试玩-麻将胡了技巧-pg麻将胡了2 副教授,硕士研究生导师。主要从事人工智能、数据挖掘与知识发现、信息素养等领域的教学与科研工作。在国内外高水平期刊和学术会议上发表论文50余篇,其中包括ESI高被引论文1篇,中山大学认定的一类重要期刊论文17篇,累计影响因子190.9,被引用1500余次。主持国家社会科学基金项目、国家自然科学基金项目、广东省社科规划项目、广州市科技菁英“领航”项目等多项。主讲并参与建设的2门信息素养教育课程先后入选国家级一流本科课程。曾获广东省科技进步奖二等奖、广东省学位与研究生教育学会优秀教育成果奖、ACM广州新星奖。
学术专长
情报学、计算机应用技术
研究方向
人工智能、数据挖掘与知识发现、信息素养、数字素养
研究经历
1. 国家社会科学基金一般项目,大中小学一体化数字素养教育内容框架与实施路径研究,主持人
2. 国家自然科学基金青年项目,面向大规模优化问题的分布式Memetic算法研究,主持人
3. 广东省哲学社会科学规划项目,乡村振兴战略下广东省农民数字素养培育内容框架与提升策略研究,主持人
4. 广东省科技计划项目,面向智能制造的智能工控平台研发与应用,中山大学项目负责人
5. 广州市科技菁英“领航”项目,数据驱动的大规模群体智能优化方法与应用,主持人
6. 中山大学青年教师培育项目,智能文本聚类方法及其在科技情报领域的应用研究,主持人
7. 中山大学青年教师起步计划项目,分布式计算智能算法研究,主持人
8. 国家社会科学基金重大项目,粤港澳大湾区建设国际科创中心知识产权情报保障研究,参与人
9. 国家社会科学基金重大项目,古籍保护学科建设与理论体系研究,参与人
10. 国家自然科学基金重点项目,分布式计算智能理论及应用,参与人
11. 国家社会科学基金一般项目,全民信息素养框架构建与提升策略研究,参与人
12. 国家自然科学基金面上项目,运用新型分布估计算法优化保险投资方案的研究,参与人
13. 国家自然科学基金面上项目,云计算多工作流调度的动态分布式粒子群优化方法研究,参与人
14. 国家自然科学基金面上项目,基于云计算的协同进化粒子群算法及应用研究,参与人
15. 国家自然科学基金青年项目,基于知识图谱的用户长尾需求建模研究,参与人
16. 国家自然科学基金青年项目,基于云计算的自适应分布式差分进化算法研究,参与人
17. 国家自然科学基金青年项目,基于云计算模型的自组织差分进化算法及其应用研究,参与人
18. 国家社科基金青年项目,技术赋能视阈下人文学者的数字学术需求及其图书馆服务策略研究,参与人
19. 教育部人文社科研究青年项目,社会化媒体用户-平台互动均衡下隐私规制机理研究,参与人
20. 广州市科技计划项目,基于大数据的急性胸痛疾病人工智能诊疗模式及关键技术研究
教育背景
2009.9至2014.6,中山大学计算机系,计算机应用技术,博士(硕博连读)
2005.9至2009.7,中山大学计算机系,网络工程,学士
著作论文
一、期刊论文
- 余维杰,史瑜君,周晟欣,杨阳.基于弹幕的动态用户画像研究——以在线教育场景为例[J/OL].情报科学.
- 杨阳,余维杰(通讯作者).融合弹幕内容特征与行为特征的用户画像研究——以B站教学类视频为例[J].情报科学,2022,40(12):161-169.
- 吴锦池,余维杰(通讯作者).融合知识库语义的文本聚类研究[J].情报杂志,2021,40(05):156-164.
- 吴锦池,余维杰(通讯作者).基于社会网络分析的政务微博影响力研究[J].情报科学,2021,39(02):78-85.
- 吴锦池,余维杰(通讯作者).图书馆数据治理成熟度评价体系构建[J].情报科学,2021,39(01):65-71.
- 余维杰,周娅莉,吴锦池.我国研究生在科研活动中的数据素养现状研究——以双生命周期理论为视角[J].图书情报工作,2020,64(07):84-93.
- 余维杰,陈思琪,陈序.国内外数据素养研究的文献计量分析[J].图书馆理论与实践,2019(12):32-39.
- Shuai Z, Liu H, Wan Z, Yu W J(余维杰), et al. A Self-adaptive neuroevolution approach to constructing Deep Neural Network architectures across different types[J]. Applied Soft Computing, 2023, 136: 110127.
- Ma Z, Zhong J, Liu W L, Yu W J(余维杰). An evolutionary framework for automatic security guards deployment in large public spaces[J]. Applied Intelligence, 2023, 53(10): 11586-11598.
- Ge Y F, Yu W J(余维杰,通讯作者), Cao J, et al. Distributed memetic algorithm for outsourced database fragmentation[J]. IEEE Transactions on Cybernetics, 2021, 51(10): 4808-4820.
- Ji J Y, Yu W J(余维杰,通讯作者), Zhong J, et al. Density-enhanced multiobjective evolutionary approach for power economic dispatch problems[J]. IEEE Transactions on Systems, Man, and Cybernetics-Systems, 2021, 51(4): 2054-2067.
- Huang S, Zhong J, Yu W J(余维杰). Surrogate-assisted evolutionary framework with adaptive knowledge transfer for multi-task optimization[J]. IEEE Transactions on Emerging Topics in Computing, 2021, 9(4): 1930-1944.
- Cong H, Chen W N, Yu W J(余维杰). A two-stage information retrieval system based on interactive multimodal genetic algorithm for query weight optimization[J]. Complex & Intelligent Systems, 2021, 7(5): 2765-2781.
- Ge Y F, Yu W J(余维杰,通讯作者), Lin Y, et al. Distributed differential evolution based on adaptive mergence and split for large-scale optimization[J]. IEEE Transactions on Cybernetics, 2018, 48(7): 2166-2180.
- Yu W J(余维杰), Shen M, Chen W N, et al. Differential evolution with two-level parameter adaptation[J]. IEEE Transactions on Cybernetics, 2014, 44(7): 1080-1099.
- Yu W J(余维杰), Ji J Y, Gong Y J, et al. A tri-objective differential evolution approach for multimodal optimization[J]. Information Sciences, 2018, 423: 1-23.
- Ji J Y, Yu W J(余维杰,通讯作者), Gong Y J, et al. Multiobjective optimization with ϵ-constrained method for solving real-parameter constrained optimization problems[J]. Information Sciences, 2018, 467: 15-34.
- Yu W J(余维杰), Li J Z, Chen W N, et al. A parallel double-level multiobjective evolutionary algorithm for robust optimization[J]. Applied Soft Computing, 2017, 59: 258-275.
- Yu W J(余维杰), Zhan Z H, Zhang J. Artificial bee colony algorithm with an adaptive greedy position update strategy[J]. Soft Computing, 2018, 22(2): 437-451.
- Wang Z J, Zhan Z H, Yu W J(余维杰), et al. Dynamic group learning distributed particle swarm optimization for large-scale optimization and its application in cloud workflow scheduling[J]. IEEE Transactions on Cybernetics, 2020, 50(6): 2715-2729.
- Wang Z J, Zhan Z H, Lin Y, Yu W J(余维杰), et al. Automatic niching differential evolution with contour prediction approach for multimodal optimization problems[J]. IEEE Transactions on Evolutionary Computation, 2020, 24(1): 114-128.
- Wang Z J, Zhan Z H, Lin Y, Yu W J(余维杰), et al. Dual-strategy differential evolution with affinity propagation clustering for multimodal optimization problems[J]. IEEE Transactions on Evolutionary Computation, 2018, 22(6): 894-908.
- Jia Y H, Chen W N, Gu T, Yu W J(余维杰), et al. A dynamic logistic dispatching system with set-based particle swarm optimization[J]. IEEE Transactions on Systems, Man, and Cybernetics-Systems, 2018, 48(9): 1607-1621.
- Jia Y H, Zhou Y R, Lin Y, Yu W J(余维杰), et al. A distributed cooperative co-evolutionary CMA evolution strategy for global optimization of large-scale overlapping problems[J]. IEEE Access, 2019, 7: 19821-19834.
- Zhang J, Chen W N, Zhan Z H, Yu W J(余维杰), et al. A survey on algorithm adaptation in evolutionary computation[J]. Frontiers of Electrical and Electronic Engineering, 2012, 7(1): 16-31.
二、会议论文
- Liu X X, Liu D, Yang Q, Liu X F, Yu W J(余维杰). Comparative Analysis of Five Local Search Operators on Visiting Constrained Multiple Traveling Salesmen Problem[C]//2021 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2021: 01-08.
- Sun B, Wang C, Yang Q, Liu W, Yu W J(余维杰). Ant colony optimization for balanced multiple traveling salesmen problem[C]//2021 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2021: 476-481.
- Yong-Feng Ge, Jinli Cao, Hua Wang, Jiao Yin, Wei-Jie Yu (余维杰,通讯作者), et al., “A Benefit-driven genetic algorithm for balancing privacy and utility in database fragmentation,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2019), 2019, pp. 167-168.
- Jing-Yu Ji, Wei-Jie Yu (余维杰,通讯作者), and Jun Zhang, “Solving Nonlinear Equation Systems Using Multiobjective Differential Evolution,” in Proc. International Conference on Evolutionary Multi-Criterion Optimization (EMO 2019), 2019, pp. 139-150.
- Yong-Feng Ge, Wei-Jie Yu (余维杰,通讯作者), Zhi-Hui Zhan, and Jun Zhang, “Competition-Based Distributed Differential Evolution,” in Proc. IEEE Congr. Evol. Comput. (CEC 2018), 2018.
- Jing-Yu Ji, Wei-Jie Yu (余维杰,通讯作者), and Jun Zhang, “A two-stage coevolution approach for constrained optimization,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2017), 2017, pp. 167-168.
- Jing-Yu Ji, Wei-Jie Yu (余维杰,通讯作者), et al., “Solving multimodal optimization problems through a multiobjective optimization approach,” in Proc. IEEE International Conference on Information Science and Technology (ICIST 2017), 2017, pp. 458-463.
- Yong-Feng Ge, Wei-Jie Yu (余维杰,通讯作者), Jing-Jing Li, Zhi-Wen Yu, and Jun Zhang, “Enhancing distributed differential evolution with a space-driven topology,” in Proc. IEEE Congr. Evol. Comput. (CEC 2016), 2016, pp. 4090-4095.
- Yong-Feng Ge, Wei-Jie Yu (余维杰,通讯作者), and Jun Zhang, “Diversity-based multi-population differential evolution for large-scale optimization,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2016), 2016, pp. 31-32.
- Wei-Jie Yu (余维杰), Jing-Jing Li, Jun Zhang, and Meng Wan, “Differential evolution using mutation strategy with adaptive greediness degree control,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2014), 2014, pp.73-80.
- Wei-Jie Yu (余维杰), Jun Zhang, and Wei-Neng Chen, “Adaptive artificial bee colony optimization,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2013), 2013, pp. 153-157.
- Wei-Jie Yu (余维杰) and Jun Zhang, “Adaptive differential evolution with optimization state estimation,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2012), 2012, pp. 1285-1292.
- Wei-Jie Yu (余维杰) and Jun Zhang, “Multi-population differential evolution with adaptive parameter control for global optimization,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2011), 2011, pp. 1093-1098.
- Wei-Jie Yu (余维杰) and Jun Zhang, “Pheromone-distribution-based adaptive ant colony system,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2010), 2010, pp. 31-38.
- Wei-Jie Yu (余维杰), Xiao-Min Hu, Jun Zhang, and Rui-Zhang Huang, “Self-adaptive ant colony system for the traveling salesman problem,” in Proc. IEEE Conf. on Syst., Man, Cybern. (SMC 2009), 2009, pp. 1399-1404.
- Zhi-Hui Zhan, Yong-Xing Wang, Zi-Jia Wang, Wei-Jie Yu (余维杰), and Jun Zhang, “Competitive Swarm Optimizer with Dynamic Grouping for Large Scale Optimization,” in Proc. IEEE Congr. Evol. Comput. (CEC 2018), 2018.
- Da-Zhao Tan, Wei-Neng Chen, Jun Zhang, and Wei-Jie Yu (余维杰), “Fast pedestrian detection using multimodal estimation of distribution algorithms,” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2017), 2017, pp. 1248-1255.
- Xin Situ, Wei-Neng Chen, Yue-Jiao Gong, Ying Lin, Wei-Jie Yu (余维杰), Zhiwen Yu, Jun Zhang, “A parallel ant colony system based on region decomposition for taxi-passenger matching,” in Proc. IEEE Congr. Evol. Comput. (CEC 2017), 2017, pp. 960-967.
- Yong-Feng Ge, Yue-Jiao. Gong, Wei-Jie Yu (余维杰), et al. “Reconstructing cross-cut shredded text documents: a genetic algorithm with splicing-driven reproduction” in Proc. ACM Genetic Evol. Comput. Conf. (GECCO 2015), 2015, pp. 847-853.
- Xiao-Min Hu, Zhi-Hui Zhan, Ying Lin, Yue-Jiao Gong, Wei-Jie Yu (余维杰), et al., “Multiobjective genetic algorithm for demand side management of smart grid,” in Proc. IEEE Symposium on Computational Intelligence in Scheduling (SCIS 2013), 2013, pp. 14-21.
获奖情况
2023年,《信息素养与信息检索通用教程》入选国家级一流本科课程
2023年,中山大学第十一届本科教育教学成果二等奖
2023年,中山大学优秀班主任
2022年,中山大学年度考核“优秀”
2021年,广东省科技进步奖二等奖
2021年,广东省学位与研究生教育学会优秀教育成果奖
2020年,《信息素养通识教程:数字化生存的必修课》入选首批国家级一流本科课程
2019年,《信息素养通识教程:数字化生存的必修课》入选国家精品在线开放课程
2019年,中山大学第九届教学成果奖二等奖
2017年,ACM广州新星奖
2017年,中山大学年度考核“优秀”
2016年,中山大学“采联”青年教师奖励金
2016年,中山大学年度考核“优秀”
工作经历
2018.4至今,pg麻将胡了试玩-麻将胡了技巧-pg麻将胡了2 ,副教授
2014.11至2018.4,pg麻将胡了试玩-麻将胡了技巧-pg麻将胡了2 ,讲师