Distinguished Associate Professor
Supervisor of Master's Candidates
Date of Employment:2025-06-25
School/Department:School of Computer Science and Engineering
Sex:Male
Status:Employed
Alma Mater:悉尼科技大学
杨浩然，男，汉族，湖南新化人，共青团员，现任中南大学计算机学院特聘副教授。2025年2月博士毕业于悉尼科技大学，师从徐贯东教授（香港教育大学助理副校长、人工智能讲座教授），期间于2023年9月至2024年12月在香港理工大学进行联合培养，导师为李青教授（IEEE Fellow，电子计算学系系主任），2020年6月本科毕业于南京大学计算机科学与技术系（现计算机学院）计算机与金融工程实验班。主要研究方向是基于图神经网络的图数据挖掘及其应用。入选中南大学2025年海归青年学者国际合作种子计划（重点资助）。近几年来，在数据挖掘、人工智能等领域的主流国际期刊和会议发表论文10余篇，代表性论文发表在相关领域的顶级国际会议和期刊如ICDM、WWW、NeurIPS、TKDE等，并在相关会议上作报告分享科研成果，其中一篇论文获CCF- C类会议ADMA2022“最佳应用论文奖”。长期担任数据挖掘、人工智能等领域顶级会议和期刊（如AAAI、IJCAI、ICDM、NeurIPS、WWW、SIGIR、TKDE、TOIS等）的程序委员和审稿人。曾受邀在CCF-C类会议WISE2021上做教学讲座（Tutorial）。
欢迎具有良好编程基础，对基于图神经网络的图数据挖掘以及相关应用感兴趣的，致力于发表高水平论文的同学联系。相关要求如下：
1、良好的理工科背景（计算机、软工、物理、金融、生信、数学等），有一定编程基础，熟练掌握PyTorch、TensorFlow等编程框架者优先；
2、态度端正，有相关科研、项目经历者优先；
3、阅读过图学习领域一些代表性论文，对该领域有基本的了解。
请将简历、成绩单以及相关成果材料（如有）发送至本人邮箱：yhr [dot] cse [AT] csu [dot] edu [dot] cn，因邮件数量过多，恕不一一回复。
本人与中国香港以及澳大利亚相关高校和科研机构保持紧密联系与合作，可推荐优秀学生前去访问、深造。
部分论文成果 (完整列表请参见Google Scholar)：
2025年及以后：
[10] Jiahao Liang#, Haoran Yang#, Xiangyu Zhao*, Yuzhi Wen, Guandong Xu, Wanyu Wang, Kaixiang Yang*, “Democratic Recommendation with User and Item Representatives Produced by Graph Condensation”, IEEE Transactions on Knowledge and Data Engineering. (共一第一为本人指导学生，Major Revision)
[9] Haoran Yang, Hongxu Chen, Xiangyu Zhao, Sixiao Zhang, Xiangguo Sun, Qian Li, Hongzhi Yin, Guandong Xu*, “Generating Compressed Counterfactual Hard Negative Samples for Graph Contrastive Learning”, CAAI Transactions on Intelligence Technology. (中科院SCI一区TOP, JCR Q1，已接收，待发表)
[8] Sirui Huang, Qian Li, Haoran Yang, Dianer Yu, Qing Li, Guandong Xu*, “Causal Time-aware News Recommendations with Large Language Models”, ACM Transactions on Information Systems, vol. 43, issue. 6, pp. 1-25, Sept. 2025, doi: 10.1145/3729422. (CCF-A, JCR Q1)
2025年之前：
[7] Haoran Yang, Yuhao Wang, Xiangyu Zhao*, Hongxu Chen, Hongzhi Yin, Qing Li, Guandong Xu*, “Multi-level Graph Knowledge Contrastive Learning”, IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 12, pp. 8829-8841, Dec. 2024, doi: 10.1109/TKDE.2024.3466530. (CCF-A, JCR Q1)
[6] Haoran Yang, Xiangyu Zhao*, Yicong Li, Hongxu Chen, Guandong Xu*, “An Empirical Study Towards Prompt-Tuning for Graph Contrastive Pre-Training in Recommendations”, The 37th Conference on Neural Information Processing Systems, New Orleans, Louisiana, USA, 11th-14th Dec 2023. (CCF-A)
[5] Haoran Yang, Xiangyu Zhao*, Muyang Li, Hongxu Chen, Guandong Xu*, “Mitigating Performance Sacrifice in DP-satisfied Federated Settings through Graph Contrastive Learning”, Information Sciences, Volume 648, 2023, 119552, ISSN 0020-0255. (CCF-B, JCR Q1)
[4] Haoran Yang#, Hongxu Chen#*, Sixiao Zhang, Xiangguo Sun, Qian Li, Xiangyu Zhao, Guandong Xu*, “Generating Counterfactual Hard Negative Samples for Graph Contrastive Learning”, The 32nd ACM Web Conference, Austin, Texas, USA, 30th April-4th May 2023. (CCF-A)
[3] Dawei Xu, Haoran Yang, Marian-Andrei Rizoiu, Guandong Xu, “Being Automated or Not? Risk Identification of Occupations with Graph Neural Networks”, The 18th International Conference on Advanced Data Mining and Applications, Brisbane, Australia, 30th Nov-2nd Dec 2022. (第一作者为本人指导学生，CCF-C, Best Application Award)
[2] Haoran Yang#, Hongxu Chen#*, Shirui Pan, Lin Li, Philip S. Yu, Guandong Xu*, “Dual Space Graph Contrastive Learning”, The 31st ACM Web Conference, Lyon, France, 25th-29th April 2022. (CCF-A)
[1] Haoran Yang#, Hongxu Chen#*, Lin Li, Philip S. Yu, Guandong Xu*, “Hyper Meta-Path Contrastive Learning for Multi-Behavior Recommendation”, The 21st IEEE International Conference on Data Mining, Auckland, New Zealand, 7th-10th December 2021. (CCF-B, 接收率: 9.9%)
