职称

教授

电子邮件

yuhang@shu.edu.cn

办公室

计1009室

研究方向

1. 自主智能决策，主要涉及多智能体感知和多智能体信息交互

2. 机器学习方法研究，主要涉及增量学习，小样本学习，以及迁移学习

3. 计算智能方法研究，主要涉及模糊计算和进化计算

4. 自然语言处理，主要涉及事件检测和知识图谱

个人简介

男，博士，现任上海大学教授，博士生导师，享受伟长学者三级待遇。2021年博士毕业于悉尼科技大学，同年进入上海大学计算机工程与科学学院工作，2022年升任上海大学教授。曾于2021年入选上海市海外高层次人才计划、上海市青年启明星计划，2022年入选国家级青年人才计划。主要工作围绕智能决策、大数据、自然语言处理等新一代信息技术进行研究，以机器学习与智能计算为核心能力重构传统服务方式，为智慧海洋，智慧法律、智慧交通、智慧医疗、智慧金融等行业提供精准、高效的智能化服务。目前以第一或通讯作者共发表SCI/EI论文60余篇，包含本领域的顶级期刊IEEE-TKDE、IEEE-TNNLS、IEEE-TFS、IEEE-TCYB和中国计算机协会推荐的A类会议ACL、AAAI、CVPR等。并担任ACL, IJCAI, AAAI, EMNLP, IJCNN等国际会议的PC，以及IEEE多个汇刊在内的特约审稿人。

个人主页：https://yuhang.netlify.app/

主要工作经历

全职

• 校对外联络处，副处长（挂职），2024/01-至今

• 上海大学计算机工程与科学学院，教授（破格晋升），2022/10-至今

• 上海大学计算机工程与科学学院，讲师，2021/04-2022/10

• 澳大利亚人工智能研究院，研究助理，2020/09-2021/04

• 小桔科技有限公司（滴滴打车），前端工程师，2016/04-2016/08

兼职

• 悉尼科技大学，Adjunct Fellow

• 浪潮新基建，技术顾问

• 中冶焦耐（大连）工程技术有限公司，技术专家

科研项目

1. 2025年01月 至 2027年12月，数字孪生驱动的铜加工生产先质量预测与控制关键技术研究，在研,主持

2. 2024年5月 至 2027年4月，基于机器学习的高危新生儿多维度临床监护智能预警系统的研发，结项, 主持

3. 2024年04月 至 2024年11月, 基于大模型的机房巡检机器人及服务平台研究，结项, 主持

4. 2024年01月 至 2026年01月, 基于焦炉生产数据流可视化分析的移动端远程运维技术研究，在研, 主持

5. 2024年01月 至 2026年12月, 金融交易行为数据流驱动的金融欺诈检测方法研究，在研, 主持

6. 2023年01月 至 2025年01月, 焦炉加热系统数字孪生平台，结项, 主持

7. 2023年04月 至 2026年03月,基于仿人视觉的单艇环境感知方法研究，在研,主持

8. 2022年08月 至 2023年12月, 地质模式约束的非均质储层精细刻画，结项, 主持

9. 2022年04月 至 2025年03月, 面向支付交易场景的异常动态行为侦测方法研究，结项, 主持

10. 2021年12月 至 2022年12月, 面向通信的人工智能信号处理技术研究，结项, 主持

代表性论文或专著

期刊论文列表

1. Zhang Z, Xie S, Zhang H, et al. Zero-shot sim-to-real transfer using Siamese-Q-Based reinforcement learning[J]. Information Fusion (五年影响因子 16.1，中科院1区), 2025, 114: 102664.

2. Su H, Xie S, Yu H, et al. Improving inference via rich path information and logic rules for document-level relation extraction[J]. Knowledge and Information Systems (CCF B), 2025: 1-25. 该论文方法在第13届国际自然语言处理与中文计算会议NLPCC竞赛中，获开放测评任务3:对话级别指代消解与关系抽取任务中第一名的好成绩。

3. Zhou X, Yu H, Yang S, et al. Learning from Orthogonal Space with Multimodal Large Models for Generalized Few-shot Segmentation[J]. ACM Transactions on Multimedia Computing, Communications and Applications (CCF B), 2025, Early Access

4. Wang X, Yu H, Guo J, et al. Towards Fraud Detection Via Fine-Grained Classification of User Behavior[J]. IEEE Transactions on Big Data (影响因子7.5), 2024, Early Access.

5. Yu H, Wen J, Sun Y, et al. CA-GNN: A Competence-Aware Graph Neural Network for Semi-Supervised Learning on Streaming Data[J]. IEEE Transactions on Cybernetics (影响因子 9.4，中科院1区), 2024, Early Access.

6. Xie S, Li Y, Wang X, et al. Hierarchical relationship modeling in multi-agent reinforcement learning for mixed cooperative–competitive environments[J]. Information Fusion (五年影响因子 16.1，中科院1区), 2024, 108: 102318.

7. Xiao W, Luo X, Xie S, et al. An Adaptive Meta-Reinforcement Learning Algorithm for Simulation to Reality in Dynamic Scene[J]. IEEE Transactions on Intelligent Vehicles (影响因子 14，中科院1区), 2024, Early Access.

8. Yu H, Liu W, Zhu N, et al. IN-GFD: An interpretable graph fraud detection model for spam reviews[J]. IEEE Transactions on Artificial Intelligence, 2024, Early Access.

9. Guo Y, Yu H, Ma L, et al. DIE-CDK: A Discriminative Information Enhancement Method with Cross-modal Domain Knowledge for Fine-grained Ship Detection[J]. IEEE Transactions on Circuits and Systems for Video Technology (影响因子 8.3，中科院1区), 2024, Early Access.

10. Zhang Y, Wei X, Yu H. HD-LJP: A Hierarchical Dependency-based Legal Judgment Prediction Framework for multi-task learning[J]. Knowledge-Based Systems (影响因子 7.2，中科院1区), 2024: 112033.

11. Guo Y, Yu H, Xie S, et al. DSCA: A Dual Semantic Correlation Alignment Method for domain adaptation object detection[J]. Pattern Recognition (影响因子 7.5，中科院1区), 2024, 150: 110329.

12. Zhang H, Yu H, Wang X, et al. Knowledge-guided communication preference learning model for multi-agent cooperation[J]. Information Sciences (CCF B，中科院1区), 2024, 667: 120395.

13. Li J, Yu H, Zhang Z, et al. Concept drift adaptation by exploiting drift type[J]. ACM Transactions on Knowledge Discovery from Data (CCF B), 2024, 18(4): 1-22.

14. Wen Y M, Liu X, Yu H. Adaptive tree-like neural network: Overcoming catastrophic forgetting to classify streaming data with concept drifts[J]. Knowledge-Based Systems (影响因子 7.2，中科院1区), 2024, 293: 111636.

15. Jin W, Zhao B, Zhang Y, et al. WordTransABSA: enhancing Aspect-based Sentiment Analysis with masked language modeling for affective token prediction[J]. Expert Systems with Applications (影响因子7.5, 中科院1区), 2024, 238: 122289.

16. Yu H, Li J, Lu J, et al. Type-LDD: A Type-Driven Lite Concept Drift Detector for Data Streams[J]. IEEE Transactions on Knowledge and Data Engineering (CCF A), 2023.

17. Jin W, Zhao B, Zhang L, et al. Back to common sense: Oxford dictionary descriptive knowledge augmentation for aspect-based sentiment analysis[J]. Information Processing & Management (影响因子 7.4，中科院1区), 2023, 60(3): 103260. 获评2023年该期刊的年度最佳论文.

18. Yu H, Liu W, Lu J, et al. Detecting group concept drift from multiple data streams[J]. Pattern Recognition (影响因子 7.5，中科院1区), 2023, 134: 109113.

19. Wang P, Yu H, Jin N, et al. QuadCDD: A quadruple-based approach for understanding concept drift in data streams[J]. Expert Systems with Applications (影响因子7.5, 中科院1区), 2024, 238: 122114.

20. Li P, Yu H, Luo X, et al. LGM-GNN: A local and global aware memory-based graph neural network for fraud detection[J]. IEEE Transactions on Big Data (影响因子7.5), 2023, 9(4): 1116-1127.

21. 文益民、员喆、余航，一种新的半监督归纳迁移学习框架：Co-Transfer, 计算机研究与发展 (计算机类三大中文刊物之一), 2023, 60(7): 1603-1614.

22. Xie S, Zhang Z, Yu H, et al. Recurrent prediction model for partially observable MDPs[J]. Information Sciences (CCF B，中科院1区), 2023, 620: 125-141.

23. Tian P, Yu H. Can we improve meta-learning model in few-shot learning by aligning data distributions?[J]. Knowledge-Based Systems (影响因子7.2, 中科院1区), 2023, 277: 110800.

24. Guo Y, Yu H, Ma L, et al. Thfe: a triple-hierarchy feature enhancement method for tiny boat detection[J]. Engineering Applications of Artificial Intelligence (影响因子7.5, 中科院1区), 2023, 123: 106271.

25. Xia N, Yu H, Wang Y, et al. DAFS: a domain aware few shot generative model for event detection[J]. Machine Learning (CCF B), 2023, 112(3): 1011-1031.

26. Jin W, Zhao B, Yu H, et al. Improving embedded knowledge graph multi-hop question answering by introducing relational chain reasoning[J]. Data Mining and Knowledge Discovery (CCF B), 2023, 37(1): 255-288.

27. Gao J, Yu H, Zhang S. Joint event causality extraction using dual-channel enhanced neural network[J]. Knowledge-Based Systems (影响因子7.2, 中科院1区), 2022, 258: 109935.

28. Yu H, Zhang Q, Liu T, et al. Meta-ADD: A meta-learning based pre-trained model for concept drift active detection[J]. Information Sciences (CCF B，中科院1区), 2022, 608: 996-1009.

29. Yu H, Lu J, Liu A, et al. Real-time prediction system of train carriage load based on multi-stream fuzzy learning[J]. IEEE Transactions on Intelligent Transportation Systems (影响因子 7.9，中科院1区), 2022, 23(9): 15155-15165.

30. Xie S, Zhang H, Yu H, et al. Et-hf: A novel information sharing model to improve multi-agent cooperation[J]. Knowledge-Based Systems (影响因子7.2, 中科院1区), 2022, 257: 109916.

31. Yu H, Lu J, Zhang G. Morstreaming: A multioutput regression system for streaming data[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems (影响因子 8.6，中科院1区), 2021, 52(8): 4862-4874.

32. Yu H, Lu J, Zhang G. Topology learning-based fuzzy random neural networks for streaming data regression[J]. IEEE Transactions on Fuzzy Systems (影响因子 10.7，中科院1区), 2020, 30(2): 412-425.

33. Yu H, Lu J, Zhang G. Continuous support vector regression for nonstationary streaming data[J]. IEEE Transactions on Cybernetics (影响因子 9.4，中科院1区), 2020, 52(5): 3592-3605.

34. Yu H, Lu J, Zhang G. An online robust support vector regression for data streams[J]. IEEE Transactions on Knowledge and Data Engineering (CCF A), 2020, 34(1): 150-163.

35. Yu H, Lu J, Zhang G. Online topology learning by a Gaussian membership-based self-organizing incremental neural network[J]. IEEE transactions on neural networks and learning systems (影响因子 10.2，中科院1区), 2019, 31(10): 3947-3961.

会议论文列表

1. Li Pengbo, Yu Hang, Luo Xiangfeng. Context-aware Graph Neural Network for Graph-based Fraud Detection with Extremely Limited Labels[C]. AAAI (CCF A), 2025.

2. Ma Q, Yu H, Shan Y, et al. Exploiting the relationship within the unlabelled samples by set matching for generalized category discovery[C]. ICASSP (语音处理领域顶会, CCF B), IEEE, 2025.

3. Liu Z, Yu H, Luo X. Federated Graph Anomaly Detection via Disentangled Representation Learning[C]. WWW (CCF A), 2025.

4. Yu H, Yu H. Enhancing Zero-Shot Knowledge Graph Relation Prediction through Large Language Models and Contrastive Learning. WWW (CCF A), 2025.

5. Gu J, Yu H, Luo X. A Masked AutoEncoder with Strong-Weak Mutual Information for Anomaly Detection in Dynamic Incomplete Graphs. (CCF A), 2025.

6. Gao JQ, Cao J, Bu RR, Zhu NJ, Guan W, Yu H. Promoting Knowledge Base Question Answering by Directing LLMs to Generate Task-relevant Logical Forms[C]. AAAI (CCF A), 2025.

7. Gao JQ, Wu H, Cheung YM, Cao J, Yu H, Zhang YG. Mitigating Forgetting in Adapting Pre-trained Language Models to Text Processing Tasks via Consistency Alignment[C]. WWW (CCF A), 2025.

8. Wei X, Chen H, Yu H, et al. Guided Knowledge Generation with Language Models for Commonsense Reasoning[C]. EMNLP (自然语言处理三大会之一, CCF B), 2024: 1103-1136.

9. Xu Q, Wei X, Yu H, et al. Divide and Conquer: Legal Concept-guided Criminal Court View Generation[C]. EMNLP (自然语言处理三大会之一, CCF B), 2024: 3395-3410.

10. Zhang R, Zhang

11. H, Yu H, et al. Approaching outside: scaling unsupervised 3D object detection from 2D scene[C]. ECCV (图像处理三大会之一, CCF B), 2024: 249-266.

12. Wei X, Xu Q, Yu H, et al. Through the MUD: A Multi-Defendant Charge Prediction Benchmark with Linked Crime Elements[C]. ACL (CCF A), 2024: 2864-2878.

13. Li J, Yu H, Luo X, et al. COSIGN: Contextual Facts Guided Generation for Knowledge Graph Completion[C]. NAACL (自然语言处理三大会之一, CCF B), 2024: 1669-1682.

14. Yu H, Liu Z, Luo X. Barely Supervised Learning for Graph-Based Fraud Detection[C]. AAAI (CCF A), 2024, 38(15): 16548-16557.

15. Yu H, Li R, Xie S, et al. Shadow-Enlightened Image Outpainting[C]. CVPR (CCF A), 2024: 7850-7860.

16. Wei X, Huang J, Yu H, et al. Ptcspell: Pre-trained corrector based on character shape and pinyin for chinese spelling correction[C]. ACL (CCF A), 2023: 6330-6343.