Jiasheng Zhang

Associate professor  

Name (Simplified Chinese):张嘉昇

Name (Pinyin):zhangjiasheng

E-Mail:

Date of Employment:2025-07-01

Education Level:With Certificate of Graduation for Doctorate Study

Gender:Male

Professional Title:Associate professor

Status:On duty

Academic Titles:菁英副教授

Alma Mater:电子科技大学

College:计算机科学与技术学院

School/Department:计算机科学与技术学院


Education Background

2024.02 -- 2025.01

耶鲁大学       Computer Science and Technology       联合培养博士生

2015.09 -- 2019.06

电子科技大学       Software Engineering       University graduated       Bachelor's Degree in Engineering

2019.09 -- 2021.06

电子科技大学       Computer Science and Technology       硕转博

2021.09 -- 2025.06

电子科技大学       Computer Science and Technology       With Certificate of Graduation for Doctorate Study       Doctoral Degree in Engineering

Work Experience

2022.07 -- 2023.03

北京滴滴科技有限公司      地图事业部      算法实习生(未来精英人才计划)

Personal Profile

张嘉昇,副教授。2019年和2025年在电子科技大学分别获得学士学位和博士学位(申恒涛教授团队,师从邵杰教授 https://cfm.uestc.edu.cn/~shaojie/)。曾在美国耶鲁大学(合作导师为图学习领域著名学者 Rex Ying https://www.cs.yale.edu/homes/ying-rex/)、北京小桔科技有限公司(滴滴出行)等机构从事研究工作。担任NeurIPS领域主席。


主持承担了四川省科技厅苗子工程重点项目、陕西省博士后科研资助(二等)等项目多项,作为项目骨干参与国自然面上、重点研发等项目。相关论文发表于SIGMOD、VLDB、ICML、NeurIPS、KDD、SIGIR、TKDE等CCF-A类期刊/会议总计30余篇,授权专利7项,软著1项,并长期承担 ICDE、KDD、ICLR、NeurIPS、ACL、CVPR、MM等顶级学术会议的程序委员。


招生简介:

本人于2025年加入西电计算机科学与技术学院 智能媒体与数据工程研究所(崔江涛教授、李辉教授团队),团队网址:https://imde.xidian.edu.cn/。本人主要研究方向聚焦知识工程与图数据挖掘核心领域,涵盖可信多模态知识抽取、时空约束下的复杂知识推理、多智能体系统构建与优化,以及大语言模型赋能的大规模图分析技术,致力于攻克领域核心技术难题,推动相关技术在智慧城市、智能制造、环境监测等关键场景的产业化落地。


诚邀本校学有余力、对人工智能与大数据挖掘抱有浓厚兴趣的本科生加入课题组。同时欢迎想要参与 “挑战杯”、中国高校计算机大赛等高水平学科竞赛的同学随时联系,我将提供全程一对一指导,助力学生夯实科研基础、提升综合能力,为后续深造与职业发展奠定坚实根基


代表论文:

[1] Zhang Jiasheng, Ouyang Deqiang, Liang Shuang, and Shao Jie. Towards pattern-aware data augmentation for temporal knowledge graph completion. Proceedings of the VLDB Endow,2025,18(10): 3573–3586. (VLDB, CCF-A)

[2] Zhang Jiasheng, Zhang Delvin Ce, Liang Shuang, Li Zhengpin, Ying Rex, Shao Jie. Retrieval-augmented language Model for knowledge-aware protein encoding. Forty-second International Conference on Machine Learning, 2025. (ICML, CCF-A)

[3] Zhang Jiasheng, Maatouk Ali, Chen Jialin, Ngoc Bui, Xie Qianqian, Leandros Tassiulas, Xu Hua, Shao Jie, Ying Rex. Litfm: A retrieval augmented structure-aware foundation model for citation graphs. Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V. 2. 2025: 3728-3739. (KDD, CCF-A)

[4] Zhang Jiasheng, Ying Rex, Shao Jie. Online detection of anomalies in temporal knowledge graphs with interpretability. Proceedings of the ACM on Management of Data, 2024, 2(6): 1-26. (SIGMOD, CCF-A)

[5] Zhang Jiasheng, Chen Jialin, Yang Menglin, Feng Aosong, Liang Aosong, Shao Jie, Ying Rex. DTGB: A comprehensive benchmark for dynamic text-attributed graphs. Advances in Neural Information Processing Systems, 2024, 37: 91405-91429. (NeurIPS, CCF-A)

[6] Zhang Jiasheng, Shao Jie, Cui Bin. Streame: Learning to update representations for temporal knowledge graphs in streaming scenarios. Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2023: 622-631. (SIGIR, CCF-A)

[7] Zhang Jiasheng, An Kaiqiang, Liu Guoping, Wen Xiang, Hu Runbo, Shao Jie. Understanding the semantics of GPS-based trajectories for road closure detection. Proceedings of the 29th ACM SIGKDD conference on knowledge discovery and data mining. 2023: 5554-5563. (KDD, CCF-A)

[8] Liang Shuang, Shao Jie, Zhang Dongyang, Zhang Jiasheng, Cui Bin. DRGI: Deep relational graph infomax for knowledge graph completion. IEEE Transactions on Knowledge and Data Engineering, 2021: 2486-2499. (TKDE, CCF-A)