Chen Gong (宫辰)'s Homepage
Welcome to my homepage! 欢迎访问我的主页!
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Chen Gong
IEEE Senior Member
Address: Room 4030, Dingxin Building, Nanjing University of Science and Technology
E-mail: chen.gong@njust.edu.cn |
Opening Positions (研究岗位)
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1. There are opening research positions in my group at all levels, including Postdoc, research assistant, Ph.D. student, and master student.
Please drop me an E-mail which contains your CV, score sheet, certificates, and representative publications if you are interested.
2. I'm always looking for self-motivated undergraduate students (mainly @NJUST) to join my group for research training!
1. 我的课题组目前有研究岗位若干，包括博士后、研究助理、博士、硕士等。如果您感兴趣，请将您的简历、成绩单、获奖证书、代表作发至我的邮箱。
2. 十分欢迎优秀的本科生（主要面向本校同学）来我的课题组参加科研训练！
Brief Biography (个人简介)
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Chen Gong is a full professor in the School of Computer Science and Engineering, Nanjing University of Science and Technology.
He received his B.E. degree from East China University of Science and Technology (ECUST) in 2010, and dual doctoral degree from Shanghai Jiao Tong University (SJTU) and University of Technology Sydney (UTS) in 2016 and 2017, respectively.
He has published more than 100 technical papers at prominent journals and conferences such as IEEE T-PAMI, IEEE T-NNLS, IEEE T-IP, IEEE T-CYB, ICML, NeurIPS, CVPR, AAAI, IJCAI, ICDM, etc, and also holds 7 granted inventory patents.
He serves as the associate editor for IEEE T-CSVT, NN, NePL, FR and CJE, reviewer for more than 30 international journals such as AIJ, JMLR, IEEE T-PAMI, IJCV, IEEE T-NNLS, IEEE T-IP,IEEE T-KDE,
and also the SPC/PC member of several top-tier conferences such as ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV, AAAI, IJCAI, ICDM, etc.
He received the "Wu Wen-Jun AI Excellent Youth Scholar Award", "Young Elite Scientists Sponsorship Program" of China Association for Science and Technology, The Science Fund for Distinguished Young Scholars of Jiangsu Province, "Hong Kong Scholar",
the second prize of Shanghai Natural Science Award, and "Excellent Doctorial Dissertation award" by Shanghai Jiao Tong University (SJTU) and Chinese Association for Artificial Intelligence (CAAI).
He was also selected to the Global Top Chinese Young Scholars in AI released by Baidu, and World's top 2% scientists list by Stanford University.
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宫辰现任南京理工大学计算机科学与工程学院教授、博导；获国家级青年人才计划、江苏省杰青。于2010年获得华东理工大学学士学位，并分别于2016、2017年获上海交通大学和悉尼科技大学双博士学位。
已在世界顶级期刊或会议上发表100余篇学术论文，主要包括IEEE T-PAMI, IEEE T-NNLS, IEEE T-IP, IEEE T-CYB, ICML, NeurIPS, CVPR, AAAI, IJCAI, ICDM等，另有7项发明专利获得授权。
目前担任国际期刊IEEE T-CSVT、NN、NePL、FR、CJE编委，AIJ、JMLR、IEEE T-PAMI、IJCV、IEEE T-NNLS、IEEE T-IP、IEEE T-KDE等30余家国际权威期刊审稿人，以及ICML、NeurIPS、ICLR、CVPR、ICCV、ECCV、AAAI、IJCAI、ICDM等多个国际会议的(S)PC member。
曾获吴文俊人工智能优秀青年奖、中国科协“青年人才托举工程”、中国人工智能学会“优秀博士学位论文”奖、上海市自然科学二等奖、上海交通大学“优秀博士学位论文”奖、江苏省“六大人才高峰”、江苏省“双创博士”、江苏省科协“青年人才托举工程”、“香江学者”等，
并入选百度发布的全球华人AI青年学者榜单、斯坦福大学发布的全球前2％顶尖科学家榜单。
News (新闻)
Our paper "Traffic Pattern Sharing for Federated Traffic Flow Prediction with Personalization" wins ICDM-2024 Best Student Paper Runner-Up Award! 论文"Traffic Pattern Sharing for Federated Traffic Flow Prediction with Personalization"获得ICDM-2024最佳学生论文提名奖！
Our paper "Robust Learning under Hybrid Noise" was accepted by ACM TIST! 论文"Robust Learning under Hybrid Noise"被ACM TIST录用！
Our paper "SpliceMix: A Cross-scale and Semantic Blending Augmentation Strategy for Multi-label Image Classification" was accepted by IEEE T-MM! 论文"SpliceMix: A Cross-scale and Semantic Blending Augmentation Strategy for Multi-label Image Classification"被IEEE T-MM录用！
I was invited to be a Senior PC Member for PAKDD 2025 我受邀担任PAKDD 2025高级程序委员会成员
Our paper "Estimating Per-Class Statistics for Label Noise Learning" was accepted by IEEE T-PAMI! 论文"Estimating Per-Class Statistics for Label Noise Learning"被IEEE T-PAMI录用！
I was invited to be an Area Chair for AISTATS 2025 我受邀担任AISTATS 2025领域主席
Our paper "Traffic Pattern Sharing for Federated Traffic Flow Prediction with Personalization" was accepted by ICDM 2024! 论文"Traffic Pattern Sharing for Federated Traffic Flow Prediction with Personalization"被ICDM 2024录用！
I was invited to be an Area Chair for ICLR 2025 我受邀担任ICLR 2025领域主席
Our paper "Prototype Learning Guided Hybrid Network for Breast Tumor Segmentation in DCE-MRI" was accepted by IEEE T-MI! 论文"Prototype Learning Guided Hybrid Network for Breast Tumor Segmentation in DCE-MRI"被IEEE T-MI录用！
Two papers on weakly-supervised knowledge distillation were accepted by ECCV and IEEE T-IP! 两篇关于弱监督知识蒸馏的论文被ECCV和IEEE T-IP录用！
I was invited to be a Senior PC Member for AAAI 2025 我受邀担任AAAI 2025高级程序委员会成员
I was honarably recognized as "Outstanding Pilot of Student Pilot Program (SPP) of China Computer Federation (CCF)"! 我获评中国计算机学会“2023-2024年度学生领航计划（SPP）优秀领航员”！
Our paper "Adaptive Discriminative Regularization for Visual Classification" was accepted by IJCV! 论文"Adaptive Discriminative Regularization for Visual Classification"被IJCV录用！
I was honarably recognized as one of the Best Associate Editors (3 among 100+ AEs) of IEEE T-CSVT for the year of 2023! 我有幸获评期刊IEEE T-CSVT 2023年度优秀编委（3/100+ AEs）！
I was invited to be an editorial board member for Fundamental Research and Chinese Journal of Electronics 我受邀担任期刊Fundamental Research及Chinese Journal of Electronics青年编委
I was invited to be an Area Chair for ICDM 2024 我受邀担任ICDM 2024领域主席
Our papers on domain adaptation, OOD generalization and noisy semi-supervised learning were respectively accepted by IEEE T-CSVT, IJCV and PR! 关于域适应、OOD泛化、带噪半监督学习的论文分别被IEEE T-CSVT、IJCV、PR录用！
Our paper "Class-wise Contrastive Prototype Learning for Semi-Supervised Classification under Intersectional Class Mismatch" was accepted by IEEE T-MM! 论文"Class-wise Contrastive Prototype Learning for Semi-Supervised Classification under Intersectional Class Mismatch"被IEEE T-MM录用！
Our paper "Faster Nonconvex Low-rank Matrix Learning for Image Low-level and High-level Vision: A Unified Framework" was accepted by Information Fusion! 论文"Faster Nonconvex Low-rank Matrix Learning for Image Low-level and High-level Vision: A Unified Framework"被Information Fusion录用！
I was invited to be an Area Chair for ECML-PKDD 2024 我受邀担任ECML-PKDD 2024领域主席
Our paper "Easy-to-Hard Domain Adaptation with Human Interaction for Hyperspectral Image Classification" was accepted by IEEE T-GRS! 论文"Easy-to-Hard Domain Adaptation with Human Interaction for Hyperspectral Image Classification"被IEEE T-GRS录用！
Congratulations to Sheng Wan for winning "Outstanding PhD thesis" of the Chinese Institute of Electronics! Big Congrats!! 祝贺万升获得中国电子学会优秀博士学位论文奖！
Our paper "Robust Similarity Learning with Difference Alignment Regularization" was accepted by ICLR 2024! 论文"Robust Similarity Learning with Difference Alignment Regularization"被ICLR 2024录用！
I was invited to be an Area Chair for IEEE CAI 2024 我受邀担任IEEE CAI 2024领域主席
Congratulations to Zhuo Huang for winning "Outstanding Master thesis" of Jiangsu Province! Big Congrats!! 祝贺黄琢获得江苏省优秀硕士学位论文奖！
Our paper "Regularly Truncated M-estimators for Learning with Noisy Labels" was accepted by IEEE T-PAMI! 论文"Regularly Truncated M-estimators for Learning with Noisy Labels"被IEEE T-PAMI录用！
Our paper "SHaRPose: Sparse High-Resolution Representation for Human Pose Estimation" was accepted by AAAI 2024! 论文"SHaRPose: Sparse High-Resolution Representation for Human Pose Estimation"被AAAI 2024录用！
I was invited to be an SPC member for PAKDD 2024, and a reviewer for ICML 2024 我受邀担任PAKDD 2024高级程序委员会成员、ICML 2024审稿人
Paper on open-set semi-supervised learning was accepted by ACM TOMM! 关于开放集半监督学习的论文被ACM TOMM录用！
I was selected as World's top 2% scientists for the year of 2023 我入选2023全球前2％顶尖科学家榜单
Our paper "Unified Framework for Faster Clustering via Joint Schatten p-norm Factorization with Optimal Mean" was accepted by IEEE T-NNLS! 论文"Unified Framework for Faster Clustering via Joint Schatten p-norm Factorization with Optimal Mean"被IEEE T-NNLS录用！
I was invited to be an Area Chair for ASITATS 2024, an SPC member for AAAI 2024, and a PC member for ICLR 2024 我受邀担任AISTATS 2024领域主席、AAAI 2024高级程序委员会成员、ICLR 2024程序委员会成员
Research (研究领域)
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My research interests lie in machine learning, data mining, and learning-based vision problems. Particularly, I'm interested in weakly-supervised learning and its applications, such as semi-supervised learning, positive-unlabeled learning, label noise learning, partial label learning, etc.
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我的研究方向主要为机器学习、数据挖掘及基于学习的计算机视觉问题。特别地，我关注弱监督学习方法及其应用，比如半监督学习、PU学习、标签噪声学习、偏标记学习等。
