Yuheng Jia(贾育衡)
Ph.D., Associate Professor
School of Computer Science and Engineering, Southeast University
I am a member of PAttern Learning and Mining(PALM) Lab.
贾育衡, 博士，副教授，博导，江苏省“双创博士”，东南大学“至善青年学者”、“紫金青年学者”。2019年获得香港城市大学(CityU)博士学位，2019-2020年任香港城市大学博士后研究员。 导师为Sam Kwong 讲席教授。2020年起在东南大学计算机科学与工程学院任职副教授。现为东南大学PALM实验室成员。曾任斯坦福大学（Stanford University）访问学者（2018年）。研究内容广泛涉及机器学习和数据表示的多个子领域，主要包括半监督学习、高维数据分析与建模、张量表示与建模、图机器学习，深度学习以及在计算机视觉、高光谱表示、社区检测等方向的一些应用。在相关研究领域的国际会议和期刊上发表学术论文60余篇，其中CCF-A/IEEE Trans 论文40余篇。担任多个国际著名期刊会议的编委、程序委员会委员和审稿人。主持多项国家自然科学基金、江苏省自然科学基金等横纵向项目。
My research interests broadly include topics in machine learning and data representation, such as semi-supervised learning, high-dimensional data modeling and analysis, low-rank tensor/matrix approximation and factorization, graph signal processing and machine learning on graphs, and deep learning as well as some related applications. I have published about 60 peer-reviewed papers in top-tier journals and conferences with respect to those topics. I defended my thesis in Nov. 2018 and officially received the Ph.D. degree in Feb. 2019 from the Computer Science Department at the City University of Hong Kong, where I was advised by Professor Sam Kwong.
2024级硕士研究生（计算机科学与工程学院、软件学院、人工智能学院）仍有1-2个名额，欢迎报名！（2024年4月7日）（申请时请备注考研成绩等必要信息、请提供个人简历和研究计划）。本实验室以科研为导向，优先接收有读博意愿的硕士研究生。
计划每年辅导2-3名本科生进行科研训练，欢迎有兴趣的同学随时报名！（请申请同学在申请时附上自己的简历）
研究生招生说明：
作为导师，我有以下承诺：
1，我深知学生的成功就是老师的成功，我会全力帮助和指导学生进步。
2，我不会安排学生做无关的事务性工作，为学生营造良好的科研环境。
3，尽全力给予学生足够的指导时间。平均每周每生一对一的指导时间（组会、面谈、网络讨论等）不少于一小时。
4，坚持师生平等，尊重学生权利。
作为我的学生，希望您可以做到:
1，科研不容瑕疵。不允许任何形式的造假，剽窃等学术不端等行为。
2，科研是一个充满痛苦和惊喜的过程，兴趣和努力是克服痛苦的良药。请务必选择自己感兴趣的方向进行科研。
3，阅读是科研的不二法门，请大量阅读并按时参加组会。
4，尽管我会尽全力帮助您，但也希望您明白：达到毕业要求以取得学位是您自己的任务。所以希望您能够努力科研，有问题及时和老师沟通。
5，导师是研究生的第一负责人，任何非常规行为，请告知导师。
Contact Information:
Office: Room 230, School of Computer Science and Engineering, Southeast University Jiulonghu Campus, Nanjing, Jiangsu, China. (东南大学九龙湖校区，计算机楼，230房间)
Email: yhjia at seu dot edu dot cn
Representative Publications:
§ [TKDE] Chongjie Si; Yuheng Jia; Ran Wang; Min-Ling Zhang; Yanghe Feng; Qu Chongxiao, Multi-label Classification with High-rank and High-order Label Correlations, IEEE Transactions on Transactions on Knowledge and Data Engineering, 2023, in press. code
§ [TNNLS] Yuheng Jia; Sirui Tao; Ran Wang; Yongheng Wang, Ensemble Clustering via Co-Association Matrix Self-Enhancement, IEEE Transactions on Neural Networks and Learning Systems, 2023, in press. code
§ [TIP] Zhihao Peng; Hui Liu; Yuheng Jia; Junhui Hou, Adaptive Attribute and Structure Subspace Clustering Network, IEEE Transactions on Image Processing, 2022, 31: 3430-3439. code
§ [TCSVT] Yuheng Jia; Hui Liu; Junhui Hou; Sam Kwong; Qingfu zhang, Multi-View Spectral Clustering Tailored Tensor Low-Rank Representation, IEEE Transactions on Circuits and Systems for Video Technology, 2021, 31(12): 4784-4797. code
§ [TNNLS] Yuheng Jia; Hui Liu; Junhui Hou; Sam Kwong, Pairwise Constraint Propagation with Dual Adversarial Manifold Regularization, IEEE Transactions on Neural Networks and Learning Systems, 2020, 31(12): 5575-5587. code
§ [AAAI] Yuheng Jia; Xiaorui Peng; Ran Wang; Ming-Ling Zhang, Long-tailed Partial Label Learning by Head Classifier and Tail Classifier Cooperation, AAAI Conference on Artificial Intelligence, 2024. code
§ [NeurIPS] Yuheng Jia; Fuchao Yang; Yongqiang Dong, Partial Label Learning with Dissimilarity Propagation guided Candidate Label Shrinkage, Thirty-seventh Conference on Neural Information Processing Systems, New Orleans, Louisiana, USA, 2023-11-28~2023-12-09. code
§ [KDD] Yuheng Jia; Chongjie Si; Min-Ling Zhang, Complementary Classifier Induced Partial Label Learning, Twenty-ninth ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA, 2023-08-06~2023-08-10, pp. 974–983. code
§ [KDD] Yuheng Jia; Jiahao Jiang; Yongheng Wang, Semantic Dissimilarity Guided Locality Preserving Projections for Partial Label Dimensionality Reduction, Twenty-ninth ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, CA, USA, 2023-08-06~2023-08-10, pp. 964–973. code
§ [ACM MM] Zhihao Peng; Hui Liu; Yuheng Jia; Junhui Hou, Attention-driven graph clustering network, ACM International Conference on Multimedia, Virtual Conference, 2021-10-20~2021-10-24, pp. 935–943. code
See the full publications on Google Scholar or my Personal Homepage.
Teaching:
Undergraduate course
Mathematical Optimization（最优化方法）
Master student course
Artificial Intelligence（人工智能）
Ph.D. student course
High-dimensional Data Analysis （高维数据分析与处理）
