Photographed at XJTU in 2016
I am a Ph.D. candidate of Department of Computer Science and Technology in Nanjing University, and a member of LAMDA Group, led by Prof. Zhi-Hua Zhou. Before that, I received my B.Eng. degree in Computer Science and Technology in June 2016 from Xi’an Jiaotong University.
Research Interests. I am interested in topics of machine learning, especially the following aspects:
- AUC Optimization: building models for maximizing AUC from clean or potentially noisy, imbalanced, not fully supervised data.
- Weakly Supervised Learning: dealing with inaccurate, incomplete, inexact supervisions, including positive-unlabeled learning, semi-supervised learning, noisy label learning, etc.
- Learning under Distribution Change: building models for tasks whose test data distribution is different from the training data distribution, including data selection bias, covariate shift, domain adaptation, etc.
arXivWeakly Supervised AUC Optimization: A Unified Partial AUC Approach2023.
arXivAUC Optimization from Multiple Unlabeled Datasets2023.
ICDMBeyond Lexical Consistency: Preserving Semantic Consistency for Program TranslationIn The 23rd IEEE International Conference on Data Mining, 2023.
AAAICooperative and Adversarial Learning: Co-Enhancing Discriminability and Transferability in Domain AdaptationIn The 37th AAAI Conference on Artificial Intelligence, 2023.
AAAISemi-Supervised Learning with Support Isolation by Small-Paced Self-TrainingIn The 37th AAAI Conference on Artificial Intelligence, 2023.
IJCAICutting the Software Building Efforts in Continuous Integration by Semi-Supervised Online AUC OptimizationIn The 27th International Joint Conference on Artificial Intelligence, 2018.
AAAISemi-Supervised AUC Optimization without Guessing Labels of Unlabeled DataIn The 32nd AAAI Conference on Artificial Intelligence, 2018.
JOSCost-Sensitive Margin Distribution Optimization for Software Bug LocalizationJournal of Software, 2017.
ICMCMusic Style Analysis among Haydn, Mozart and Beethoven: an Unsupervised Machine Learning ApproachIn The 43rd International Computer Music Conference, 2017.
Worked on mining from spatial-temporal big data, for user analysis, potential customer discovery, and commercial location recommendation.
- Pattern Recognition Letter
- ACTA AUTOMATICA SINICA
Conference PC Member
- CCML 2019, AAAI 2019
- IJCAI 2020, ECAI 2020
- IJCAI 2021
- IJCAI 2022, ICML 2022, NeurIPS 2022
- AAAI 2023, PAKDD 2023
Awards & Honors
Room 912, Computer Science Building, Xianlin Campus of Nanjing University
National Key Laboratory for Novel Software Technology,
Nanjing University, Xianlin Campus Mailbox 603,
163 Xianlin Avenue, Qixia District,
Nanjing 210023, China