信息管理与管理科学系

【个人简介】

吴李康 博士，硕导，于2024年6月获得中国科学技术大学计算机应用技术专业博士学位，于2024年秋季学期加入天津大学管理与经济学部，信息管理与信息系统专业。近5年来，在国内外数据管理与挖掘和人工智能领域的顶级会议和期刊上发表论文40多篇，其中包括20余篇一作、通讯论文(含共一)，引用1700余次-单篇最高引650余次(据2025.10)，例如IEEE TKDE、IEEE TEVC、Scientific Report、Tourism Management、Pattern Recognition、ACM TKDD、IP&M、ICML、ACM SIGKDD、AAAI、IJCAI、ACM SIGIR等CCF推荐A类期刊会议、管理科学ABS高质量期刊、或中科院高分区SCI期刊。担任IJOC、TM、IEEE TPAMI、IEEE TKDE、ICML、ACM SIGKDD、ACM SIGIR、NeurIPS、ICLR等多个高水平期刊及会议审稿人、领域主席或PC。研究工作主要集中在大模型复杂决策、数据挖掘与信息管理学科的交叉领域，利用大模型技术、图表示学习算法和知识图谱分析市场行为数据，为管理决策提供有效支持，并且具有丰富的工业界合作交流经历，如联想、小米、快手、蚂蚁金服、BOSS直聘等，申请和授权国家发明专利10多项。于2023年6月发布大语言模型应用在推荐系统中的首篇综述，提出的三种LLM4Rec(LLM4RS)建模范式在业界取得了广泛的影响。入选2025中国人工智能学会-社会计算新星学者，荣获机器学习与数据挖掘领域国际顶级竞赛KDD CUP 2019特等奖，金融时间序列建模相关研究成果入选CCF A类中文期刊《计算机研究与发展》“2019高引论文Top 10奖”及“ESI高被引论文”。欢迎学界、业界同仁共同开展产学研合作。谷歌学术(Google Scholar)：https://scholar.google.com/citations?hl=en&user=QCykGDUAAAAJ&view_op=list_works&sortby=pubdate

【教育与工作经历】

【部分期刊论文】

[1] Lei Zhang, Meng Zhu, Yuanyuan Ge, Haipeng Yang, Likang Wu, Multi-Party Multi-Objective Optimization for Discrete Problems: A Case Study on Multi-Stakeholder Recommendation, IEEE Transactions on Evolutionary Computation, 2025 (ABS 4)

[2] Yuanyuan Ge, Likang Wu, Lei Zhang, Haipeng Yang, Hongke Zhao, MORA-LLM: Enhancing Multi-Objective Optimization Recommendation Algorithm by Integrating Large Language Models, IEEE Transactions on Evolutionary Computation, 2025 (ABS 4)

[3] Wenhui Liu, Likang Wu, Hongke Zhao, Improving sentiment analysis in tourism through LLM-enhanced irony detection, Tourism Management, 2026 (ABS 4)

[4] Hongke Zhao, Yuanpei Sui, Likang Wu. Exploring the interpretability of vision GCN with a multi-method approach. Expert Systems with Applications, 127624. (学部A类，FMS C类期刊)

[5] Lei Zhang, Wuji Zhang, Likang Wu, Hongke Zhao. GCTN: Graph Competitive Transfer Network for Cross-Domain Multi-Behavior Prediction. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE). (IF:6.97, JCR Q1, CCF A类期刊)

[6] Zhong Guan, Likang Wu, Hongke Zhao, Ming He, Jianping Fan, Enhancing collaborative semantics of language model-driven recommendations via graph-aware learning, IEEE Transactions on Knowledge and Data Engineering, 2025 (CCF A)

[7] Jun Wang, Likang Wu, Qi Liu, Yu Yang. An efficient continuous control perspective for reinforcement-learning-based sequential recommendation. Knowledge-Based Systems.

[8] Jiang, Junji, Likang Wu, Zhipeng Hu, Runze Wu, Xudong Shen, and Hongke Zhao. "Knowledge enhanced graph contrastive learning for match outcome prediction." Information Processing & Management 62, no. 3 (2025): 104010. (ABS2)

[9] Lv, Bing, Junji Jiang, Likang Wu, and Hongke Zhao. "Team formation in large organizations: A deep reinforcement learning approach." Decision Support Systems 187 (2024): 114343. (ABS3)

[10] Qingyang Mao, Zhi Li, Likang Wu, Qi Liu, Promoting Machine Abilities of Discovering and Utilizing Knowledge in a Unified Zero-shot Learning Paradigm, ACM Transactions on Knowledge Discovery from Data (TKDD), 19(1), 1-26, 2024. (IF4.16, JCR Q1, CCF/FMS B类期刊)

[11] Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, Hengshu Zhu, Qi Liu, Hui Xiong, Enhong Chen, A survey on large language models for recommendation, World Wide Web, 27(5), 60.

[12] Ping Ni, Xianquan Wang, Bing Lv, Likang Wu, GTR: An Explainable Graph Topic-Aware Recommender for Scholarly Document, Electronic Commerce Research and Applications (ECRA), 101439, 2024. (ABS2)

[13] 王慜懋，赵洪科，吴李康，焦之贤，黄振亚，语言模型增强的引文网络连边因子挖掘，大数据，(2096-0271), 11(2). (CCF T2类期刊)

[14] Likang Wu, Zhi Li, Hongke Zhao, Zhenya Huang, Yongqiang Han, Junji Jiang, Enhong Chen, Supporting Your Idea Reasonably: A Knowledge-Aware Topic Reasoning Strategy for Citation Recommendation, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 36(8):4275-4289, 2024. (IF:6.97, JCR Q1, CCF A类期刊)

[15] Likang Wu, Hongke Zhao, Zhi Li, Zhenya Huang, Qi Liu, Enhong Chen. 2023. Learning the Explainable Semantic Relations via Unified Graph Topic-Disentangled Neural Networks. ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 17.8 (2023): 1-23. (CCF B Journal)

[16] Likang Wu, Zhi Li, Hongke Zhao, Qi Liu, Enhong Chen. 2022. Estimating fund-raising performance for start-up projects from a market graph perspective. Pattern Recognition, 121 (2022): 108204. (JCR Q1, CCF B Journal)

[17] Junji Jiang, Likang Wu (Co-first author), Hongke Zhao, Hengshu Zhu, Wei Zhanga. 2023. Forecasting movements of stock time series based on hidden state guided deep learning approach. Information Processing & Management (IPM), 60.3 (2023): 103328. (JCR Q1, CCF B, ESI高被引论文)

[18] Hongke Zhao, Likang Wu (First student author) , Zhi Li, Xi Zhang, Qi Liu, Enhong Chen, et al. 2019. Predicting the Dynamics in Internet Finance Based on Deep Neural Network Structure. Journal of Computer Research and Development, 56.8 (2019): 1621-1631. Top 10 Papers Highly Cited Award in Journal of Computer Research and Development (CCF Chinese A Journal)

[29] Lei Zhang, Wuji Zhang, Likang Wu, Ming He, Hongke Zhao. 2023. HGCN: Socially Enhanced Heterogeneous Graph Convolutional Network for Multi-Behavior Prediction. ACM Transactions on the Web 18.1 (2023): 1-27. (CCF B Journal)

[20] Jiahui Wang, Likang Wu, Hongke Zhao, Ning Jia. 2023. Multi-view enhanced zero-shot node classification. Information Processing & Management, 60.6 (2023): 103479. (JCR Q1, CCF B Journal).

此外，POM、IJOC等多篇UTD论文二轮以上返修中，更多具体信息见个人主页，https://www.adm-cube.online/people/teacher/likang_wu

【部分会议论文】

[1] Zhong Guan, Likang Wu, Hongke Zhao, Ming He, Jianpin Fan, Attention Mechanisms Perspective: Exploring LLM Processing of Graph-Structured Data, ICML 2025 (CCF A)

[2] Xianquan Wang, Likang Wu, Zhi Li, Haitao Yuan, Shuanghong Shen, Huibo Xu, Yu Su. Mitigating Redundancy in Deep Recommender Systems: A Field Importance Distribution Perspective. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2025. (CCF A类会议)

[3] Liping Liu, Chunhong Zhang, Likang Wu, Chuang Zhao, Zheng Hu, Ming He, Jianping Fan. Instruct-of-Reflection: Enhancing Large Language Models Iterative Reflection Capabilities via Dynamic-Meta Instruction. NAACL 2025.

[4] Zipeng Liu, Likang Wu (Co-first author), Ming He, Zhong Guan, Hongke Zhao(赵洪科), Nan Feng, Multi-View Empowered Structural Graph Wordification for Language Models, 39th AAAI Conference on Artificial Intelligence (AAAI'25), Philadelphia, Pennsylvania, USA, Accepted.(CCF A)

[5] Yanmin Dong, Zhenya Huang, Guanhao Zhao, Hongke Zhao, Likang Wu, Binbin Jin, Yixia Zhao, Qi Liu. Enhancing Code Search Intent with Programming Context Exploration. In Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining (WSDM’24), 2024.

[6] Runqi Yang, Liu Yu, Zhi Li, Shaohui Li, and Likang Wu. "Rethinking Offline Reinforcement Learning for Sequential Recommendation from A Pair-Wise Q-Learning Perspective." In 2024 International Joint Conference on Neural Networks (IJCNN), pp. 1-9. IEEE, 2024.

[7] Xianquan Wang, Likang Wu, Shukang Yin, Zhi Li, Yanjiang Chen, hufeng, Yu Su, Qi Liu, I-AM-G: Interest Augmented Multimodal Generator for Item Personalization, EMNLP 2024

[8] Zhijun Dong, Likang Wu (Co-first author), Kai Zhang, Ye Liu, Zhi Li, Hongke Zhao, Enhong Chen, FZR: Enhancing Knowledge Transfer via Shared Factors Composition in Zero-Shot Relational Learning, In Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM '2024). (CCF B Conference)

[9] Likang Wu, Zhaopeng Qiu, Zhi Zheng, Hengshu Zhu, Enhong Chen. Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI '24). (CCF A Conference)

[10] Likang Wu, Zhi Li, Hongke Zhao, Zhefeng Wang, Qi Liu, Baoxing Huai, Nicholas Jing Yuan, and Enhong Chen. 2023. Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '23), pp. 2618–2628. (CCF A Conference)

[11] Likang Wu, Junji Jiang, Hongke Zhao, Hao Wang, et al. 2023. KMF: Knowledge-Aware Multi-Faceted Representation Learning for Zero-Shot Node Classification. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI '23), pp. 2361-2369 (CCF A Conference)

[12] Likang Wu, Hao Wang, Enhong Chen, Zhi Li, Hongke Zhao, Jianhui Ma. 2022. Preference Enhanced Social Influence Modeling for Network-Aware Cascade Prediction. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '22), pp. 2704-2708. (CCF A Conference)

[13] Likang Wu, Zhi Li, Hongke Zhao, Zhen Pan, Qi Liu, Enhong Chen. 2020. Estimating Early Fundraising Performance of Innovations via Graph-Based Market Environment Model. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI '20), pp. 6396-6403. (CCF A Conference)

[14] Likang Wu, Zhi Li, Hongke Zhao, Qi Liu, Mengdi Zhang, Enhong Chen. 2021. Learning the Implicit Semantic Representation on Graph-Structured Data. In Proceedings of the Database Systems for Advanced Applications (DASFAA '21), Part I 26, pp. 3-19. (CCF B Conference)

[15] Yang Yu, Qi Liu, Likang Wu, Runlong Yu, Lei Yu, Zaixi Zhang. 2023. Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI '23), pp. 4854-4863. (CCF A Conference)

[16] Yongqiang Han, Hao Wang, Kefan Wang, Likang Wu, Zhi Li, Wei Guo, Yong Liu, Defu Lian, Enhong Chen, Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation, Proceedings of the ACM on Web Conference 2024 (WWW 2024). (CCF A Conference)

[17] Qingyang Mao, Qi Liu, Zhi Li, Likang Wu, Bing Lv, Zheng Zhang, Cross-reconstructed Augmentation for Dual-target Cross-domain Recommendation, Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024). (CCF A Conference)

[18] Yixiao Ma, Shiwei Tong, Ye Liu, Likang Wu, et al. 2021. Enhanced Representation Learning for Examination Papers with Hierarchical Document Structure. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '21), pp. 2156-2160. (CCF A Conference)

[19] Zhi Li, Bo Wu, Qi Liu, Likang Wu, Hongke Zhao, Tao Mei. 2020. Learning the Compositional Visual Coherence for Complementary Recommendations. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI '20), pp. 3536–3543. (CCF A Conference)

[20] Yongqiang Han, Likang Wu, Hao Wang, Guifeng Wang, Mengdi Zhang, Zhi Li, Defu Lian, et al. 2023. GUESR: A Global Unsupervised Data-Enhancement with Bucket-Cluster Sampling for Sequential Recommendation. In Proceedings of the Database Systems for Advanced Applications (DASFAA '23), pp. 286-296. (CCF B Conference)

【所获奖项】

[1] 入选2025中国人工智能学会社会计算新星学者(讲者论坛) (2025.08)

[2] 博士研究生国家奖学金 (2023.10)

[3] 环球数码奖学金 (2022.12)

[4] 《计算机研究与发展》(CCF A 中文期刊) 2019年TOP 10高引用论文 (2020.12)

[5] 硕士研究生国家奖学金 (2020.10)

[5] KDD CUP 2019 Regular ML Track PaddlePaddle 特等奖 (2019.08)

[6] 2018快手用户兴趣建模大赛优胜奖 (Top 10) (2018.08)

[7] ACM/ICPC 大学生程序设计竞赛亚洲区域赛铜牌，全国邀请赛二等奖 (2016.10)

【承担科研项目】

1.国家自然科学基金青年项目(C)面向推荐领域的大模型复杂意图挖掘研究与应用 (2026-2028， 主持人)

2.天津大学自主创新项目-社会影响力 (2025-2026， 主持人)

3.智能互联系统安徽省实验室自主创新项目 (2025-2027， 主持人)

4.天津市教委社科重大项目子课题，(2024-2027， 主持人)

5.中国人工智能学会 CAAI-联想蓝天科研基金，AI Agent中复杂任务的可控性分解 (2024-2025， 主持人)

6.天津市自然科学基金-青年项目B-大模型驱动的金融市场动态分析与应用研究 (2024-2026， 主持人)

7.安徽省面上基金 (2025-2028， 主持)

8.基于图挖掘的相关应用，横向项目，合作单位：美团点评，华为诺亚 (2021 - 2023，参与)

9.科技部国家重点研发计划大数据知识工程，基于情景感知的知识导航 (2019.08 - 2021.12, 参与)

等

【学术与社会服务】

Conference Program Committee (PC):

ICLR(AC), NeurIPS, ICLR, AAAI, KDD, WWW, SIGIR, WWW, IJCAI, KDD, SIGIR, IJCAI, CICAI, etc

Journal Reviewer:

IJOC, TM, IEEE TPAMI, IEEE TKDE, ACM TKDD, ACM TOIS, IEEE TNNLS, IEEE TKDE, IEEE TNNLS, IPM, Frontiers of Computer Science, etc