刘永皓，吉林大学计算机科学与技术学院准聘副教授，博士生导师。主要研究方向为图表征学习、生物信息学与大语言模型，围绕图神经网络、空间多组学建模及相关智能计算方法开展研究。
近年来，在人工智能与生物信息学领域取得了一系列研究成果，以第一作者或通讯作者身份在Nature Methods、ACM TKDD，以及 NeurIPS、KDD、WWW、SIGIR、AAAI、IJCAI、EMNLP等国际顶级期刊和会议发表学术论文十余篇。同时，受邀担任 NeurIPS、ICML、KDD、WWW、SIGIR、ACL、AAAI 等国际顶级学术会议审稿人。
课题组长期致力于人工智能前沿技术与生命科学交叉研究，注重学生科研创新能力与独立研究能力的培养，为学生提供高水平科研训练、国际学术交流以及产业合作机会。课题组与国内外知名高校及头部科技企业保持良好的合作关系，鼓励并支持学生参与国际顶级期刊与会议投稿与交流。
每年计划招收博士研究生1名、硕士研究生3名，欢迎具备以下特点的优秀同学加入：
(1) 对科学研究充满热情，具有探索未知问题的兴趣；
(2) 具备良好的执行力、编程能力和独立思考能力；
(3) 具有较好的英文文献阅读与学术写作能力；
课题组鼓励并支持博士研究生高质量成果导向培养，为优秀博士生创造提前毕业条件；支持硕士研究生赴知名企业实习交流，并为硕博研究生提供具有竞争力的科研补助。
本人在攻读博士期间已与多名硕博士研究生开展深度合作，指导学生在人工智能与生物信息学领域国际顶级会议和期刊发表多篇高水平论文，积累了丰富的人才培养经验。
欢迎对图表征学习、大语言模型、生物信息学及交叉学科研究感兴趣的同学联系交流，共同开展具有国际影响力的前沿研究。
代表性工作 (*第一作者，#通讯作者，完整文章列表可见谷歌学术)
一、国际期刊
[1] Yonghao Liu*, Chuyao Wang*, Zhikang Wang*, Liang Chen, Zhi Li, Jiangning Song, Qi Zou, Rui Gao, Binzhi Qian, Xiaoyue Feng#, Renchu Guan#, Zhiyuan Yuan#. High-Parameter Spatial Multi-Omics through Histology-Anchored Integration. Nature Method. 2026. 23(2):373-386. (IF=32.1).
[2] Yonghao Liu, Mengyu Li, Ximing Li, Lan Huang, Fausto Giunchiglia, Xiaoyue Feng#, Renchu Guan#, Meta-GPS++: Enhancing Graph Meta-Learning with Contrastive Learning and Self-Training. ACM Transactions on Knowledge Discovery from Data, 2024, 18(9):1-30. (TKDD, CCF B类期刊)
二、国际会议
[1] Yonghao Liu, Lan Huang, Bowen Cao, Ximing Li, Fausto Giunchiglia, Xiaoyue Feng#, Renchu Guan#. A Simple but Effective Approach for Unsupervised Few-Shot Graph Classification. Proceedings of the ACM on Web Conference. Singapore, 13-17 May, 2024, 4249-4259. (WWW2024, CCF A类会议)
[2] Yonghao Liu, Mengyu Li, Fausto Giunchiglia, Lan Huang, Ximing Li, Xiaoyue Feng#, Renchu Guan#. Dual-level Mixup for Graph Few-shot Learning with Fewer Tasks. Proceedings of the ACM on Web Conference. Australia, 28 April-2 May 2025, 2646-2656. (WWW2025, CCF A类会议)
[3] Yonghao Liu, Fausto Giunchiglia, Ximing Li, Lan Huang, Xiaoyue Feng#, Renchu Guan#. Enhancing Graph Few-shot Learning via Set Functions and Optimal Transport. Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V. 1. Canada, 3-7 August, 2025, 871-882. (KDD2025, CCF A类会议)
[4] Yonghao Liu*, Yajun Wang*, Chunli Guo*, Wei Pang, Ximing Li, Fausto Giunchiglia, Xiaoyue Feng#, Renchu Guan#. Graph Few-Shot Learning via Adaptive Spectrum Experts and Cross-Set Distribution Calibration. The Thirty-ninth Annual Conference on Neural Information Processing Systems. San Diego, USA, 2-7 December, 2025, 160490-160517. (NeurIPS2025, CCF A类会议)
[5] Mengyu Li*, Yonghao Liu*, Fausto Giunchiglia, Ximing Li, Xiaoyue Feng#, Renchu Guan#. Simple-Sampling and Hard-Mixup with Prototypes to Rebalance Contrastive Learning for Text Classification. Proceedings of the ACM on Web Conference. Dubai, 13-17 April, 2026, 3698-3708. (WWW2026, CCF A类会议)
[6] Yonghao Liu, Mengyu Li, Ximing Li, Fausto Giunchiglia, Xiaoyue Feng#, Renchu Guan#. Few-shot Node Classification on Attributed Networks with Graph Meta-learning. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. Madrid, Spain, 11-15 July, 2022, 471-481. (SIGIR2022, CCF A类会议)
[7] Yonghao Liu, Lan Huang, Fausto Giunchiglia, Xiaoyue Feng#, Renchu Guan#. Improved Graph Contrastive Learning for Short Text Classification. Proceedings of the AAAI Conference on Artificial Intelligence, Vancouver, Canada, 20-27 February, 2024, 18716-18724. (AAAI2024, CCF A类会议)
[8] Yonghao Liu*, Mengyu Li*, Wei Pang, Ximing Li, Fausto Giunchiglia, Lan Huang, Xiaoyue Feng#, Renchu Guan#. Boosting Short Text Classification with Multi-Source Information Exploration and Dual-Level Contrastive Learning. Proceedings of the AAAI Conference on Artificial Intelligence. Philadelphia, USA, 25 February-4 March, 24696-24704. (AAAI2025, CCF A类会议)
[9] Yonghao Liu, Fausto Giunchiglia, Lan Huang, Ximing Li, Xiaoyue Feng#, Renchu Guan#. A Simple Graph Contrastive Learning Framework for Short Text Classification. Proceedings of the AAAI Conference on Artificial Intelligence, Philadelphia, USA, 25 February-4 March, 19015-19023. (AAAI2025, CCF A类会议)
[10] Renchu Guan, Yajun Wang, Chunli Guo, Bowen Cao, Fausto Giunchiglia, Wei Pang, Yonghao Liu#, Xiaoyue Feng#. Advancing Graph Few-Shot Learning via In-Context Learning. Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2. Jeju, Republic of Korea, 9-13 August, 2026, 1-12. (KDD2026, CCF A类会议)
[11] Xiaosong Han, Ke Chen, Xindi Dai, Di Liang, Minlong Peng, Wei Pang, Fausto Giunchiglia, Xiaoyue Feng#, Yonghao Liu#, Renchu Guan#. TRACE: Discovering Task-Specific Parameter via Adaptation-Aware Probing for Continual Fine-Tuning. Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2. Jeju, Republic of Korea, 9-13, August, 2026, 1-12. (KDD2026, CCF A类会议)
学术评审
CCF A类会议：NeurIPS、ICML、KDD、WWW、ACL、SIGIR、AAAI
CCF B类会议：IJCAI、EMNLP、NAACL
承担项目
[1] 国家自然科学基金委员会，面上项目，62372209，“心脏再生复杂动态系统的空间单细胞组学分析算法研究”，2024-01至2027-12, 在研，参与。
[2] 科技部，国家重点研发计划课题，2021YFF1201203，“研究生物医学知识图谱自动构建和更新技术体系”，2021-12至2024-11，结项，参与。
[3] 国家自然科学基金委员会，面上项目，62172187，“基于单细胞与空间转录组融合数据的细胞分化关键算法研究”，2022-01至2025-12，结项，参与。
优秀合作学生 (姓名-年级-文章-实习经历)
1. 陈同学，2025级硕士，KDD x 1，京东广告智能部
2. 戴同学，2025级硕士，KDD x 1，字节懂车帝->阿里通义实验室
3. 王同学，2025级硕士，NeurIPS x 1，KDD x 1，小红书应用算法部
4. 郭同学，2025级硕士，NeurIPS x 1，KDD x 1，新浪机器学习算法部
5. 李同学，2025级硕士，NeurIPS在投，滴滴金融风险部
6. 齐同学，2025级硕士，Briefings in Bioinformatics x 1，本组读博
7. 王同学，2025级硕士，Briefings in Bioinformatics x 1，腾讯TEG云架构平台部
