Chen Gong (宫辰)'s Homepage


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Chen Gong

IEEE Senior Member
Professor, PhD Supervisor (教授、博导)
School of Computer Science and Technology
Nanjing University of Science and Technology
南京理工大学计算机科学与工程学院

Address: Room 4030, Dingxin Building, Nanjing University of Science and Technology
No. 200, Xiaolingwei Street, Xuanwu, Nanjing, Jiangsu, China, 210094
通讯地址:中国江苏省南京市玄武区孝陵卫街200号南京理工大学鼎新楼4030室
邮编:210094

E-mail: chen.gong@njust.edu.cn
[Google Scholar (谷歌学术)] [University Website (学校主页)] [dblp]


Opening Positions (研究岗位)

    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)

    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 and NePL, 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 seleted to the Global Top Chinese Young Scholars in AI released by Baidu.
    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IEEE T-CSVT、NePL副编委,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。


News (新闻)

  • I was invited to be an Area Chair for ACM MM 2023 and ACML 2023
    我受邀担任ACM MM 2023及ACML 2023领域主席

  • Congratulations to Mr. Sheng Wan for successfully defending his PhD thesis!
    祝贺万升通过博士学位论文答辩!

  • I was invited to be a reviewer for NeurIPS 2023
    我受邀担任NeurIPS 2023审稿人

  • I was invited to be an SPC member/Meta-reviewer for ECAI 2023 and ECML-PKDD 2023
    我受邀担任ECAI 2023及ECML-PKDD 2023 高级程序委员会成员

  • Our paper "Robust Generalization against Corruptions via Worst-Case Sharpness Minimization" was accepted by CVPR 2023!
    论文"Robust Generalization against Corruptions via Worst-Case Sharpness Minimization"被CVPR 2023录用!

  • I was invited to be a PC Member for ICDM 2023
    我受邀担任ICDM 2023程序委员会成员

  • Our paper "KRADA: Known-region-aware Domain Alignment for Open-set Domain Adaptation in Semantic Segmentation" was accepted by TMLR!
    论文"KRADA: Known-region-aware Domain Alignment for Open-set Domain Adaptation in Semantic Segmentation"被TMLR录用!

  • Our paper "Harnessing Out-Of-Distribution Examples via Augmenting Content and Style" was accepted by ICLR 2023!
    论文"Harnessing Out-Of-Distribution Examples via Augmenting Content and Style"被ICLR 2023录用!

  • Our paper "Hyperspectral Image Classification With Contrastive Graph Convolutional Network" was accepted by IEEE T-GRS!
    论文"Hyperspectral Image Classification With Contrastive Graph Convolutional Network"被IEEE T-GRS录用!

  • I was invited to be an Associate Editor of IEEE T-CSVT
    我受邀担任IEEE T-CSVT编委

  • I was invited to be a PC Member for ICML 2023
    我受邀担任ICML 2023程序委员会成员

  • Mingyu Li and Zicheng Zhao won the 3rd prize of Jittor AI competition! Congrats!
    课题组李明语、赵子成获计图人工智能挑战赛三等奖!祝贺!

  • 1 paper on OOD data detection and 1 paper on contrastive learning were accepted by NeurIPS 2022!
    关于分布外数据检测及对比学习的论文被NeurIPS 2022接收!

  • I was promoted to IEEE Senior Member!
    我晋升为IEEE高级会员!

  • Congratulations to Zhuo Huang for winning "JSAI outstanding master thesis" award!
    祝贺黄琢姚垚获得江苏省人工智能学会优秀硕士论文奖!

  • Our paper "Tackling Micro-Expression Data Shortage via Dataset Alignment and Active Learning" was accepted by IEEE T-MM!
    论文"Tackling Micro-Expression Data Shortage via Dataset Alignment and Active Learning"被IEEE T-MM录用!

  • 1 paper on label noise learning and 1 paper on low-rank matrix recovery were respectively accepted by MLJ and IEEE T-NNLS!
    关于标签噪声学习及低秩矩阵恢复的论文分别被MLJ、IEEE T-NNLS录用!

  • I was invited to be a Senior PC Member for ACML 2022
    我受邀担任ACML 2022高级程序委员会成员

  • 1 paper on label noise learning, 1 paper on semi-supervised learning, and 1 paper on adversarial training were respectively accepted by IEEE T-PAMI, IEEE T-MM, and ICML 2022!
    关于标签噪声学习、半监督学习、对抗学习的论文分别被IEEE T-PAMI、IEEE T-MM、ICML 2022录用!

  • Our paper "Enhanced Spatial-Temporal Salience for Cross-view Gait Recognition" was accepted by IEEE T-CSVT!
    论文"Enhanced Spatial-Temporal Salience for Cross-view Gait Recognition"被IEEE T-CSVT录用!

  • I was selected into the list of high-potential young Chinese scholars in AI released by Baidu!
    我入选百度发布的高潜力AI华人青年学者榜单!

  • Our paper "Multi-Level Graph Learning Network for Hyperspectral Image Classification" was accepted by PR!
    论文"Multi-Level Graph Learning Network for Hyperspectral Image Classification"被PR录用!

  • Our paper "Feature Integration-based Training For Cross-domain Hyperspectral Image Classification" was accepted by IGARSS 2022!
    论文"Feature Integration-based Training For Cross-domain Hyperspectral Image Classification"被IGARSS录用!

  • I was invited to be a PC Member for ICDM 2022
    我受邀担任ICDM 2022程序委员会成员

  • I was invited to be a PC Member for CIKM 2022
    我受邀担任CIKM 2022程序委员会成员

  • Our paper "Consistency and Diversity induced Human Motion Segmentation" was accepted by IEEE T-PAMI!
    论文"Consistency and Diversity induced Human Motion Segmentation"被IEEE T-PAMI录用!

  • I was invited to be a Senior PC Member for IJCAI 2022
    我受邀担任IJCAI 2022高级程序委员会成员

  • Our paper "Multi-class Label Noise Learning via Loss Decomposition and Centroid Estimation" was accepted by SDM 2022!
    论文"Multi-class Label Noise Learning via Loss Decomposition and Centroid Estimation"被SDM 2022录用!

  • Congratulations to Yao Yao for winning "JSAI outstanding master thesis" award!
    祝贺姚垚获得江苏省人工智能学会优秀硕士论文奖!

  • Shuo Chen's and Jingchen Ke's theses were selected as "Outstanding Doctorial/Master thesis" of Jiangsu Province! Big Congrats!
    祝贺陈硕和柯京辰分别获得江苏省优秀博士和优秀硕士学位论文!

  • Our paper "Dynamic Spectral-Spatial Poisson Learning for Hyperspectral Image Classification with Extremely Scarce Labels" was accepted by IEEE T-GRS!
    论文"Dynamic Spectral-Spatial Poisson Learning for Hyperspectral Image Classification with Extremely Scarce Labels"被IEEE T-GRS录用!

  • Our paper "Understanding How Pre-Training Regularizes Deep Learning Algorithms" was accepted by IEEE T-NNLS!
    论文"Understanding How Pre-Training Regularizes Deep Learning Algorithms"被IEEE T-NNLS录用!

  • Sheng Wan, Zhendong Wang, Zhenyuan Chen and Yuhao Wang were awarded the national scholarship! Congrats!
    课题组万升、王振东、陈震元、王禹淏荣获国家奖学金!祝贺!

  • 3 papers on semi-supervised learning and adversarial learning were accepted by NeurIPS 2021!
    课题组3篇关于半监督学习和对抗学习的论文被NeurIPS 2021录用!

  • Our paper "Reliable Shot Identification for Complex Event Detection via Visual-Semantic Embedding" was accepted by CVIU!
    论文"Reliable Shot Identification for Complex Event Detection via Visual-Semantic Embedding"被CVIU录用!

  • Our paper "Multiscale Dynamic Graph Convolutional Network for Hyperspectral Image Classification" was selected as a ESI highly cited paper!
    论文"Multiscale Dynamic Graph Convolutional Network for Hyperspectral Image Classification"被评选为ESI高被引论文(本领域世界前1%的论文)!

  • Our paper "Fraud Detection under Multi-Sourced Extremely Noisy Annotations" was accepted by CIKM 2021!
    论文"Fraud Detection under Multi-Sourced Extremely Noisy Annotations"被CIKM 2021录用!

  • I was invited to be a Senior PC Member for AAAI 2022
    我受邀担任AAAI 2022高级程序委员会成员

  • Our paper "Hyperspectral Image Classification With Context-Aware Dynamic Graph Convolutional Network" was selected as a ESI highly cited paper!
    论文"Hyperspectral Image Classification With Context-Aware Dynamic Graph Convolutional Network"入选ESI高被引论文(本领域世界前1%的论文)!

  • Our paper "Estimating Human Pose Efficiently by Parallel Pyramid Networks" was accepted by IEEE T-IP!
    论文"Estimating Human Pose Efficiently by Parallel Pyramid Networks"被IEEE T-IP录用!

  • I was invited to be a reviewer for AISTATS 2022
    我受邀担任AISTATS 2022审稿人

  • Our group won the 1st place of CVPR 2021 Learning from Imperfect Data (LID) challenge (Weakly-supervised Object Localization Track), and the 3rd place in the Weakly-supervised Semantic Segmentation Track!
    团队获得CVPR 2021不完备数据竞赛弱监督目标定位项目冠军及弱监督语义分割项目季军!

  • Our paper "Edge-aware Multi-scale Feature Integration Network for Salient Object Detection in Optical Remote Sensing Images" was accepted by IEEE T-GRS!
    论文"Edge-aware Multi-scale Feature Integration Network for Salient Object Detection in Optical Remote Sensing Images"被IEEE T-GRS录用!

  • I was invited to be a reviewer for ICLR 2022
    我受邀担任ICLR 2022审稿人

  • Our paper "Modeling Cardinality in Image Hashing" was accepted by IEEE T-CYB!
    论文"Modeling Cardinality in Image Hashing"被IEEE T-CYB录用!

  • Shuo Chen's thesis was selected as "Outstanding PhD thesis" of NJUST! Jingchen Ke's thesis was selected as "Outstanding Master thesis" of NJUST! Big congratulations!
    祝贺课题组陈硕获得南理工优秀博士学位论文!柯京辰获得南理工优秀专业硕士学位论文!

  • Our paper "SDOF-GAN: Symmetric Dense Optical Flow Estimation with Generative Adversarial Networks" was accepted by IEEE T-IP!
    论文"SDOF-GAN: Symmetric Dense Optical Flow Estimation with Generative Adversarial Networks"被IEEE T-IP录用!

  • Our paper "Large-Margin Contrastive Learning with Distance Polarization Regularizer" was accepted by ICML 2021!
    论文"Large-Margin Contrastive Learning with Distance Polarization Regularizer"被ICML 2021录用!

  • Our paper "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning" was accepted by IJCAI 2021!
    论文"Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning"被IJCAI 2021录用!

  • Our paper "Dual Interactive Graph Convolutional Networks for Hyperspectral Image Classification" was accepted by IEEE T-GRS!
    论文"Dual Interactive Graph Convolutional Networks for Hyperspectral Image Classification"被IEEE T-GRS录用!

  • I was invited to be a Senior PC member for ACML 2021, and PC member for CIKM 2021
    我受邀担任ACML 2021 Senior PC member以及CIKM 2021 PC member

  • I was invited to be a reviewer for NeurIPS 2021
    我受邀担任NeurIPS 2021审稿人

  • Our paper "Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning" was accepted by IEEE T-NNLS!
    论文"Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning"被IEEE T-NNLS录用!

  • Our paper "Instance-Dependent Positive and Unlabeled Learning with Labeling Bias Estimation" was accepted by IEEE T-PAMI!
    论文"Instance-Dependent Positive and Unlabeled Learning with Labeling Bias Estimation"被IEEE T-PAMI录用!

  • I was invited to be a reviewer for ECML-PKDD 2021
    我受邀担任ECML-PKDD 2021审稿人

  • I gave a keynote speech at International Conference on Electronics, Circuits and Information Engineering 2021.
    我在ECIE 2021大会上作主旨报告

  • I was invited to be a reviewer for ICIP 2021
    我受邀担任ICIP 2021审稿人

  • Our paper "Robust Early-Learning: Hindering the Memorization of Noisy Labels" was accepted by ICLR 2021!
    论文"Robust Early-Learning: Hindering the Memorization of Noisy Labels"被ICLR 2021录用!

  • I was invited to be a reviewer for ICCV 2021
    我受邀担任ICCV 2021审稿人

  • Our paper "Cost-Sensitive Positive and Unlabeled Learning" was accepted by Information Sciences!
    论文"Cost-Sensitive Positive and Unlabeled Learning"被Information Sciences录用!

  • Jingchen Ke's thesis won "JSAI outstanding master thesis candidate" award
    柯京辰的硕士论文获得江苏省人工智能学会优秀硕士论文提名奖

  • I was invited to be a reviewer for IJCV
    我受邀担任IJCV审稿人

  • I gave a talk at Southeast University
    我在东南大学作学术报告

  • Our paper "Centroid Estimation with Guaranteed Efficiency: A General Framework for Weakly Supervised Learning" was accepted by IEEE T-PAMI!
    论文"Centroid Estimation with Guaranteed Efficiency: A General Framework for Weakly Supervised Learning"被IEEE T-PAMI录用!

  • I was invited to be a reviewer for ICML 2021
    我受邀担任ICML 2021审稿人

  • Hong Shi won the "Software Scholarship" of Jiangsu province!
    毕业生史红获得江苏软件奖学金!

  • Our papers "Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning", "Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model" and "Learning with Group Noise" were accepted by AAAI 2021!
    课题组3篇论文"Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning"、"Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model"、"Learning with Group Noise" 被AAAI 2021接收!


Research (研究领域)

    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.
    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。


Sponsors (资助机构)

NSFC Ant-Financial CASC NJUST TENCENT HUAWEI