阎岩，教授，博士生导师，2021年于西北工业大学计算机学院获得博士学位。加拿大卡尔顿大学计算机科学系国家公派留学生，博士后。2024年入选太阳成集团tyc138青年拔尖人才 B1 岗，担任教授。近五年以第一作者发表CCF推荐学术论文十余篇。主持国家自然科学基金青年项目、太阳成集团tyc138引进人才科研资助专项；作为科研骨干参与国家及省部级重点研发项目。受邀担任TPAMI、AIJ、TKDD、TNNLS、TCYB、ICML、NeurIPS、ICLR、IJCAI等多个国际顶级期刊和会议的审稿人。

偏标记学习 (Partial Label Learning)、多标记学习 (Multi-Label Learning)、域适应 (Domain Adaptation)、联邦学习 (Federated Learning)、表示学习 (Representation Learning)

欢迎计算机相关专业同学报考博士和硕士研究生！欢迎感兴趣的本科生提前进组参与科研学习！

招生要求：

[1] 热爱科研，有良好的自我驱动力！

[2] 具有良好的数学基础、英文读写能力以及编程能力！

近五年第一作者代表性成果：

[1] Y. Yan and Y. Guo. Federated Partial Label Learning with Local-Adaptive Augmentation and Regularization, In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI-24) (CCF-A).

[2] Y. Yan and Y. Guo. Partial Label Unsupervised Domain Adaptation with Class-Prototype Alignment, In Proceedings of the 11th International Conference on Learning Representations (ICLR-2023) (清华A类).

[3] Y. Yan and Y. Guo. Mutual Partial Label Learning with Competitive Label Noise, In Proceedings of the 11th International Conference on Learning Representations (ICLR-2023) (清华A类).

[4] Y. Yan and Y. Guo. Adversarial Partial Multi-Label Learning with Label Disambiguation, In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI-21). (CCF-A).

[5] Y. Yan and Y. Guo. Multi-level Generative Models for Partial Label Learning with Non-random Label Noise, International Joint Conference on Artificial Intelligence (IJCAI-21). (CCF-A).

[6] Y. Yan and Y. Guo. Partial Label Learning with Batch Label Correction, In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI-20), pages 6575–6582, 2020. (CCF-A).

[1] 国际会议程序委员会成员：ICML 2021-2024; NeurIPS 2022-2023; ICLR 2023-2024; IJCAI 2024;  ECML 2022-2024; ECAI 2023-2024;

[2] 国际期刊审稿人：Transactions on Pattern Analysis and Machine Intelligence、Artificial Intelligence、ACM Transactions on Knowledge Discovery from Data、IEEE Transactions on Neural Networks and Learning Systems、IEEE Transactions on Cybernetics、Information Sciences、Knowledge-based Systems