张志宏 副教授、硕士、博士生导师

软件工程系副主任

Ph.D. 英国约克大学计算机学院 (最佳博士论文)2013.03

研究方向:人工智能,图神经网络,以新能源为主体的新型电力系统,能源系统数字化智能化

电子邮件:zhihong@xmu.edu.cn

个人主页:

个人简历:

教育背景

  • 2013年3月 博士 毕业于英国约克大学计算机学院 (荣获最佳博士论文)

  • 2009年6月 学士 毕业于英国阿尔斯特大学计算机学院(荣获First Class Honour)


工作经历

  • 2019.06 – 至今     厦门大学信息学院 副教授、博士生导师

  • 2016.08 - 2019.06   厦门大学软件学院 副教授

  • 2013.07 - 2016.07   厦门大学软件学院 助理教授


研究领域

生成式人工智能,图神经网络,检索增强生成(RAG)技术,能源系统数字化智能化


演讲/授课

深度学习技术,模式识别,大数据分析,生成式人工智能技术及应用


对接国家或地方战略需求,承担科技攻关科研情况

构建基于图的结构模式识别算法研究为核心、以能源领域的具体问题为交叉应用的完整研究体系。团队目前有在读博士生16名,硕士生27名。在AI for Science的背景下,依托厦门大学国家特色化示范性软件学院,联合嘉庚创新实验室和储能领域福建本土领军企业宁德时代、科华数能以及国家电网,开展智慧能源的相关研究,实现科研成果的落地应用。研究紧密围绕国家、福建省对智慧能源建设和创新应用的重大需求,以电力系统、人工智能、电化学等多学科交叉为基础,以技术创新为驱动力,主攻储能电池电解液性能预测及配方优化、储能电池系统智能化管控、能源互联网智能优化调度、电力设备运检处置推理、电力网络信息安全等技术创新。


重要学术组织任职及重要学术报告

1. 担任模式识别领域权威期刊 Pattern Recognition 副主编 (一区期刊)

2. 担任中国电工技术学会能源智慧化专业委员会委员

3. 担任福建省电机工程学会电力人工智能专委会 副主任委员


代表性科研项目

1. 面向可重构电池网络储能系统的动态图学习理论研究,国家自然科学基金面上项目,57万,2022.01-2025.12,在研,主持

2. 基于边云协同的区域能源互联网优化运行智能理论与关键技术,国家自然科学基金智能电网联合基金重点支持项目,254万,2021.01-2024.12,课题负责人,获优秀结题

3. 基于多模态知识增强生成式大模型与智能代理的电力生产安全管控关键技术研究及产业化,厦门市重大科技计划项目,750万,2024.07-2026.12,高校负责人

4. 基于源网荷储一体化的数字孪生关键技术研究及产业化,厦门市重大科技计划项目,500万,2022.07-2024.12,高校负责人,已结题

5. “车-桩-网”深度耦合下的“车-桩”充电引导与“桩-网”建设规划研究,国家电网,在研,主持

6. 面向敏感数据访问行为的数据库数据安全异常实时监测技术研究,国家电网,在研,主持

7. 智慧能源大数据关键技术研究,科华数能,在研,主持

8. 基于认知图谱的电网主设备智慧诊断关键技术研究与应用,国家电网,已结题,主持

9. 基于知识-数据双驱动事件图谱的配网智能决策关键技术研究,国家电网,已结题,主持

10. 面向电网企业代理购电的复杂因素多时空尺度电力供需预测及交易策略研究,国家电网,已结题,主持

11. 基于大数据分析的国网西安数据中心能效诊断系统平台的研究及应用,国家电网,已结题,主持


获奖状况

  • 2025年田昭武学科交叉奖一等奖

  • 2021年福建省科技进步二等奖

  • 2020年厦门市科技进步二等奖

  • 2018年获得国际模式识别重要会议ICPR 2018最佳论文奖“Best Scientific Paper Award”

  • 2017年入选厦门市重点人才

  • 2015年入选厦门市第七批高层次人才项目“双百计划”


代表性论文

1. Qichuan Liu,Chentao Zhang, Chenfeng Zheng,Xiaodong Li, Guosheng Hu, Zhihong Zhang(通讯作者), Beyond the Answer: Advancing Multi-Hop QA with Fine-Grained Graph Reasoning and Evaluation, In Proceedings of ACL, 2025. (CCF A类会议)

2. Jingwei Hu, Kai Xie, Zheng Fang, Xiaodong Li, Junchi Yan, Zhihong Zhang(通讯作者), Optimize Battery Control: A Multi-Objective Evolutionary Ensemble Reinforcement Learning Approach, In Proceedings of IJCAI, 2025. (CCF A类会议)

3. Qiyao Huang, Yingyue Zhang, Zhihong Zhang(通讯作者), and Edwin Hancock, ESSEN: Improving Evolution State Estimation for Temporal Networks using Von Neumann Entropy, In Proceedings of NeurIPS, 2023. (CCF A类会议)

4. Jingwei Hu, Xiaodong Li, Zheng Fang, Jun Cheng, Longqiang Yi, Zhihong Zhang(通讯作者), Estimate State of Charge in Lithium-ion Batteries with Unknown Data, Applied Energy, 2025. (JCR一区期刊,IF:10.1)

5. Jingwei Hu, Xinjie Li, Xiaodong Li, Zhensong Hou, Zhihong Zhang(通讯作者), Optimizing reinforcement learning for large action spaces via generative models: Battery pattern selection, Pattern Recognition, vol.160, 111194, 2025. (JCR一区期刊,IF:7.5)

6. Xing AiChengyu SunZhihong Zhang(通讯作者), and Edwin Hancock, Two-Level Graph Neural Network, IEEE Transactions on Neural Networks and learning systems (IEEE TNNLS),2022.(JCR一区期刊,IF11.683)

7. Zhihong Zhang, Dongdong Chen, Jianjia Wang, Lu Bai, and Edwin Hancock, Graph Motif Entropy For Understanding Time-Evolving Networks, IEEE Transactions on Neural Networks and learning systems (IEEE TNNLS),2021.(JCR一区期刊,IF11.683)

8. Zhihong Zhang, Ruiyang Liang, Xu Chen, Xuexin Xu, Guosehng Hu, Wangmeng Zuo and Edwin Hancock, Semi-Supervised Face Frontalization in the Wild, IEEE Transactions on Information Forensics & Security (IEEE TIFS),vol.16, pp.909-922,2021. (CCF A类期刊,IF6.211)

9. Zhihong Zhang, Xu Chen, Beizhan Wang, Guosheng Hu, Wangmeng Zuo and Edwin Hancock, Face Frontalization using Appearance Flow based Convolutional Neural Network, IEEE Transactions on Image Processing(IEEE TIP), 28(5): 2187-2199, 2019. (CCF A期刊,IF6.79)

10. Lu Bai, lixin Cui, Lixiang Xu, Yue Wang, Zhihong Zhang(通讯作者), and Edwin Hancock, Entropic Dynamic Time Warping Kernels for Co-evolving Financial Time Series Analysis, IEEE Transactions on Neural Networks and learning systems (IEEE TNNLS),2021. (JCR一区期刊,IF11.683)

11. Jinhui Chen, Zhihong Zhang (通讯作者) et al. Polar Transformation on Image Features for Orientation-Invariant Representations, IEEE Transactions on Multimedia(IEEE TMM), 21(2): 300-313,2019. (JCR一区期刊IF5.452)

12. Xuexin Xu, Zhihong Zhang (通讯作者) et al., Any-to-Any Voice Conversion With Multi-Layer Speaker Adaptation and Content Supervision, IEEE/ACM Transactions on Audio, Speech, and Language Processing(IEEE TASLP), 31: 3431-3445, 2023. (JCR一区期刊,IF:5.4)

13. Jiangbing Mao, Zhihong Zhang (通讯作者) et al. MGRAG: MultiModal Grid-Aware Retrieval Augmentation Generation Framework for Power Grid Work Tickets, Pattern Recognition, 2025. (JCR一区期刊,IF7.5)

14. Deng Pan, Zhihong Zhang (通讯作者) et al. Advancing Evolution Characterization in Dynamic Networks: A Quantum Walk and Thermodynamics Perspective, Pattern Recognition, 2025. (JCR一区期刊,IF7.5)

15. Dongdong Chen, Zhihong Zhang (通讯作者) et al. Thermodynamic Motif Analysis for Directed Stock Market Networks,Pattern Recognition, 2021. (JCR一区期刊,IF7.74)

16. Jianjia Wang, Zhihong Zhang (通讯作者) et al. Statistical Mechanical Analysis for Unweighted and Weighted Stock Market Networks,Pattern Recognition, 2021. (JCR一区期刊,IF7.74)

17. Jinhui Chen, Zhihong Zhang (通讯作者) et al. Multimodal Fusion for Indoor Sound Source Localization,Pattern Recognition, 2021. (JCR一区期刊,IF7.74)

18. Zhihong Zhang, Yangbin Zeng,Lu Bai and Edwin Hancock, Spectral Bounding: Strictly Satisfying the 1-Lipschitz Property for Generative Adversarial Networks, Pattern Recognition, volume 105:2020. (JCR一区期刊,IF7.74)

19. Zhihong Zhang, Dongdong Chen, Zeli Wang, Lu Bai, Heng Li and Edwin Hancock, Depth-based Subgraph Convolutional Auto-Encoder for Network Representation Learning, Pattern Recognition, 90:363-376,2019. (JCR一区期刊,IF7.74)

20. Zhihong Zhang, Dongdong Chen, Jianjia Wang, Lu Bai and Edwin Hancock, Quantum-based Subgraph Convolutional Neural Networks, Pattern Recognition,88:38-49,2019. (JCR一区期刊,IF7.74)

21. Xu Chen, Zhihong Zhang (通讯作者), Beizhan Wang, Guosheng Hu and Edwin Hancock, Recovering Variations in Facial Albedo from Low Resolution Images, Pattern Recognition, 74:373-384,2018. (JCR一区期刊,IF7.74)

22. Zhihong Zhang, Lu Bai, Yuanheng Liang and Edwin Hancock, Joint Hypergraph Learning and Sparse Regression for Feature Selection, Pattern Recognition,63: 291-309 2017. (JCR一区期刊,IF7.74)

23. Xu Chen, Zhihong Zhang (通讯作者) et al. A Graph-based Approach to Automated EUS Image Layer Segmentation and Abnormal Region Detection, Neurocomputing,336:79-91 2019. (JCR二区期刊,IF4.072)

24. Chuanyu Xu, Zhihong Zhang (通讯作者) et al. Depth-based Subgraph Convolutional Neural Networks, in Proceedings ICPR 2018. (ICPR Best Scientific Paper Award)

25. Lu Bai, Zhihong Zhang (通讯作者), C Wang, X Bai and Edwin Hancock. A Graph Kernel Based on the Jensen-Shannon Representation Alignment. In Proceedings of IJCAI, 3322-3328, 2015. (CCF A类会议)

26. Lu Bai, L Rossi, Zhihong Zhang (通讯作者) and Edwin Hancock. An Aligned Subtree  Kernel for Weighted Graphs. In Proceedings of ICML, 30-39, 2015. (CCF A类会议)

27. Xuexin Xu, Liang Shi, Jinhui Chen, Xunquan Chen, Jie Lian, Pingyuan Lin, Zhihong Zhang (通讯作者), Edwin R. Hancock. Two-Pathway Style Embedding for Arbitrary Voice Conversion, in Proceedings of INTERSPEECH 2021.