陈杰

职称:副教授
电话:0755-26038894
办公室:A317
Email:jiechen2019 at pku dot edu dot cn
实验室网站:
研究方向:1、深度学习; 2、计算机视觉与模式识别; 3、医学图像分析;4、自然语言处理;5、AI4Science。
职称 副教授 电话 0755-26038894
办公室 A317 Email jiechen2019 at pku dot edu dot cn
研究方向 1、深度学习; 2、计算机视觉与模式识别; 3、医学图像分析;4、自然语言处理;5、AI4Science。 实验室网站

研究领域和方向:

北京大学信息工程学院副教授,博士毕业于哈尔滨工业大学,先后在芬兰奥卢大学,美国马里兰大学和杜克大学工作。他致力于多模态数据(例如图像、文本等)的特征分析研究,共发表学术论文100+篇,包括Nature子刊,TPAMI,IJCV,CVPR,ICCV,ECCV和NeurIPS等,谷歌学术引用达到6500余次,入选“全球前2%顶尖科学家”榜单,其中最高单篇引用达到1700余次,次高引用1200余次。任TVCJ编委,TPAMI和IJCV客座主编,CVPR,ICCV,ECCV,ACM MM的研讨会主席,AAAI的SPC等学术职务,获得国际知名蛋白质结构预测比赛CAMEO第一名。 近五年先后主持/参与国家科技部重大基础设施、工信部5G项目建设,国家自然科学基金项目,广东重点项目,广东应急项目10+项。获得了国家科技进步二等奖两次(2005, 2015),2021年获聘深圳市鹏城孔雀特聘岗位人才。

近年承担及参与的主要科研项目:

  •  国家科技部 鹏城云脑网络智能重大科技基础设施 , PCL2021A13,2021-06至 2023-6, 2165.14 万,在研,课题负责人

  •  深圳市发改委,大规模医疗健康仿真系统,4339.50万元,鹏城实验室云脑II平台软件,实验室团队项目负责人

  •  国家自然科学基金,61972217, 小样本复杂场景图像的结构解析与学习, 2020/1/1—2023/12/31

  •  广东省联合基金重点项目,2019B1515120049, 大规模图像数据库增量计算理论与系统,2020/1/1—2022/12/31

  •  广东省防控新型冠状病毒感染科技攻关应急专项,2020B1111340056,小样本新型冠状肺炎的多模态可解释性早期诊断,2020-2至2021-6,800万

  •  深圳市政府资助,医学大数据库收集与医学图像分析,2018/6/1-2020/12/31

  •  国家自然科学基金, 61671427, 弱监督视觉目标检测, 2017/1/1—2020/12/31

  •  University of Oulu, Finland, Heart ratio measurement from VIS lighting conditions, 2015/3/1-2015/4/31

  •  国家自然科学基金, 61271433, 多视角多姿态人体目标检测, 2013/1/1-2016/12/31

  •  University of Oulu, Finland, Local descriptor for face recognition, 2012/9/1-2012/11/31

  •  Academy of Finland, Affective human-robot interaction, 01/2009 - 12/2018

  •  Finland Tekes, Joint Research in Face Analysis and Visual Surveillance (JointFavis), 04/2008 - 03/2010

  •  Academy of Finland, Texture analysis in machine vision, 09/2007- 12/2018

授课

  • 人工智能,北京大学深圳研究生院,2022

  • 人工智能,北京大学深圳研究生院,2021

  • 人工智能,北京大学深圳研究生院,2020

  • 人工智能,北京大学深圳研究生院,2019

  • 医学图像理论及其实践,北京大学深圳研究生院,2022

  • 医学图像理论及其实践,北京大学深圳研究生院,2021

  • 医学图像理论及其实践,北京大学深圳研究生院,2020

  • 医学图像理论及其实践,北京大学深圳研究生院,2019

  • 深度学习及其应用, University of Oulu, Finland, 2018.

  • 深度学习及其应用, University of Oulu, Finland, 2017.

  • 深度学习及其应用, University of Oulu, Finland, 2015.

  • 计算机图形学,University of Oulu, Finland, 2010-2016 (助教,部分内容教学)

学术荣誉

  • 中国第一届生物测定学竞赛(BVC2004)人脸验证竞赛第一名

  • IAPR ICB 2006 人脸验证竞赛第一名,该竞赛由英国University of Surrey的Josef Kittler 组织。

  • 2005年国家科技进步二等奖,获奖项目:人脸识别理论、技术、系统及其应用

  • 2015年国家科技进步二等奖,获奖项目:视觉模式的局部建模及非线性特征获取理论与方法研究

  • 2022年获得国际知名蛋白质结构预测比赛CAMEO第一名

发表的主要学术论文

署名作者文章100+篇,包括Nature 子刊,TPAMIIJCVTIPCVPRICCVECCVNIPS等。根据Google Scholar 统计,到20228月初为止,文献被引用次数达6,500+次。详细的论文列表见链接:

https://scholar.google.fi/citations?user=ZAZFfwwAAAAJ&hl=en  


部分刊物论文

[1] J. Chen, S. Shan, C. He, G. Zhao, M. Pietikäinen, X. Chen, and W. Gao. WLD: A Robust Local Image Descriptor. IEEE Trans. on Pattern Analysis and Machine Intelligence. 32(9):1705-1720,  2010 (SCI: 24)(引用排名在AI领域从20102014的五年内的所有文献中排名第56,数据是基于WoS Core的统计)(TPAMI)(国际顶级期刊)(引用1200余次)

[2] Xiawu Zheng, Rongrong Ji, Qiang Wang, Yuhang Chen, Baochang, Zhang, Jie Chen, Qixiang Ye, Feiyue Huang, Yonghong Tian, MIGO-NAS: Towards Fast and Generalizable Neural Architecture Search, IEEE Trans. on Pattern Analysis and Machine Intelligence. (已录用) (SCI: 24) TPAMI)(国际顶级期刊)

[3]    M. Pietikainen, L. Liu, J. Chen, X. Wang, G. Zhao, R. Chellappa, Compact and Efficient Feature Representation and Learning in Computer Vision, Editorial for a special issue on IEEE Trans. on Pattern Analysis and Machine Intelligence, 2018 (SCI: 24) TPAMI

[4]    R. Wang, S. Shan, X. Chen, J. Chen, and W. Gao. Maximal Linear Embedding for Dimensionality Reduction. IEEE Trans. on Pattern Analysis and Machine Intelligence. 33(9):1776-1792, 2011 (72 citations by Google Scholar) (SCI: 24) TPAMI)(国际顶级期刊)

[5] L. Liu, W. Ouyang, X. Wang, P. Fieguth, J. Chen, X.Liu, M. Pietikainen, Deep Learning for Generic Object Detection: A Survey, International Journal of Computer VisionIJCV2020, (SCI: 13)1700+ citations by Google Scholar

[6]    L. Liu, J. Chen, P. Fieguth, G. Zhao, R. Chellappa, M. Pietikainen, From BoW to CNN: Two Decades of Texture Representation for Texture Classification, International Journal of Computer Vision 2019 (IJCV)  (SCI: 13)

[7]    J. Chen, R. Wang, S. Yan, S. Shan, X. Chen, and W. Gao. Enhancing Human Face Detection by Resampling Examples through Manifolds. IEEE Trans. on System Man, and Cybernetics. 37(6):1017-1028, 2007.11 (39 citations by Google Scholar) (SCI: 13) (TSMC) (国际顶级期刊)

[8]    W. Ke, J. Chen, J. Jiao, G. Zhao, Q. Ye, SRN: Side-output Residual Network for Object Symmetry Detection in the Wild, IEEE Transactions on Neural Networks and Learning Systems, 2018 (SCI: 14) TNNLS

[9]    Ce Li, Chunyu Xie, Baochang Zhang, Jungong Han, Xiantong Zhen, Jie Chen; "Memory Attention Networks for Skeleton-based Action Recognition, IEEE Transactions on Neural Networks and Learning Systems   2021, (SCI: 14) TNNLS

[10] J. Chen, G. Zhao, M. Salo, E. Rahtu, and M. Pietikäinen, Automatic Dynamic Texture Segmentation Using Local Descriptors and Optical Flow, IEEE Trans. on Image Processing, 2013 (73 citations by Google Scholar) (SCI: 11) TIP)(国际顶级期刊)

[11] S. Xie, S. Shan, X. Chen, and J. Chen, Fusing Local Patterns of Gabor Magnitude and Phase for Face Recognition, IEEE Trans. on Image Processing, 19(5), pp: 1349-1361, 2010, (430 citations by Google Scholar) (SCI: 11) (引用排名在AI领域从20102014五年内的所有文献中排名第225,数据是基于WoS Core的统计)(TIP) (国际顶级期刊)

[12] L. Liu, J. Chen, G. Zhao, P. Fieguth, X. Chen, M. Pietikäinen, Texture Classification in Extreme Scale Variations using GANet, IEEE Trans. Image Processing, (SCI: 11) (TIP) (国际顶级期刊)

[13] Q. Liu, X. Hong, B. Zou, J. Chen, Z. Chen, Hierarchical Contour Closure based Holistic Salient Object Detection, IEEE Transactions on Image Processing, 2017 (SCI: 11) (TIP) (国际顶级期刊)

[14] Y. Xu, X. Hong, J. Chen, X. Liu, F. Porikli, G. Zhao, Saliency Integration: An Arbitrator Model, IEEE Transactions on Multimedia, 2019 (SCI: 8.1)TMM)(国际顶级期刊)

[15] Jiancheng Cai, Han Hu, Jiyun Cui, Jie Chen, Li Liu, S.Kevin Zhou; Semi-supervised Natural Face De-occlusion IEEE Transactions on Information Forensics & Security (SCI: 7.2) (TIFS), 2020(国际顶级期刊)

[16] J. Chen, X. Chen, J. Yang, S. Shan, R. Wang, and W. Gao, Optimization of a training set for more robust face detection, Pattern recognition, 41(11):2828-2840, 2009 (43 citations by Google Scholar) (SCI: 8.5) (PR) (国际顶级期刊)

[17] X. Qi, G. Zhao, J. Chen, M. Pietikäinen, Exploring Illumination Robust Descriptors for Human Epithelial Type 2 Cell Classification, Pattern Recognition, 2016 (SCI: 8.5) (PR) (国际顶级期刊)

[18] Huang, Lun; Wang, Wenmin; Xia, Yaxian; Chen, Jie; ", Adaptively aligned image captioning via adaptive attention time, Advances in Neural Information Processing Systems NIPS),2019   (国际顶级会议)

[19] Lun Huang, Wenmin Wang, Jie Chen and Xiao-Yong Wei, Attention on Attention for Image Captioning. In IEEE International Conference on Computer Vision (ICCV), 2019. (Oral) (国际顶级会议)(400+citations by Google Scholar)

[20] Can ZhangMeng CaoDongming YangJie ChenYuexian Zou; " Learn to Compare: Localize Actions under Weak Supervision, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)2021 (国际顶级会议)

[21] Qiong Wu, Pingyang Dai, Jie Chen, Chia-Wen Lin, Yongjian Wu, Feiyue Huang, Bineng Zhong, Rongrong Ji;  Discover Cross-Modality Nuances for Visible-Infrared Person Re-IdentificationProceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021  (国际顶级会议)

[22] Y. Zhai, S. Lu, Q. Ye, X. Shan, J. Chen, R. JiY. TianAD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identificationThe Conference on Computer Vision and Pattern Recognition (CVPRGoogle 统计计算机视觉&模式 识别领域影响力最高的刊物) 2020 (国际顶级会议)

[23] Q. Ye, T. Zhang, Q. Qiu, B. Zhang, J. Chen, and G. Sapiro, Self-learning Scene-specific Pedestrian Detectors using a Progressive Latent Model, IEEE International Conference on Computer Vision and Pattern Recognition, 2017  (CVPR) (国际顶级会议)

[24] W. Ke, J. Chen, J. Jiao, G. Zhao, Q. Ye,  SRN: Side-output Residual Network for Object Symmetry Detection in the Wild, IEEE International Conference on Computer Vision and Pattern Recognition, 2017 (Oral, 1.72% 录用率)  (CVPR) (国际顶级会议)

[25] X. Li, J. Chen, G. Zhao and M. Pietikäinen, Remote heart rate measurement from face videos under realistic situations. IEEE International Conference on Computer Vision and Pattern Recognition, 2014. (400+ citations by Google Scholar) (CVPR) (国际顶级会议)

[26] J. Chen, D. Yi, J. Yang, G. Zhao, S. Li, and M. Pietikäinen, Learning Mappings for Face Synthesis from Near Infrared to Visual Light Images, IEEE International Conference on Computer Vision and Pattern Recognition, 2009  (116 citations by Google Scholar, Google 统计计算机视觉&模式识别领域影响力最高的刊物) (CVPR) (国际顶级期刊)

[27] J. Chen, S. Shan, G. Zhao, X. Chen, W. Gao, and M. Pietikäinen. A Robust Descriptor based on Weber's Law. IEEE International Conference on Computer Vision and Pattern Recognition, CVPR 2008 (74 citations by Google Scholar) (CVPR) (国际顶级会议)

[28] S. Yan, S. Shan, X. Chen, W. Gao, and J. Chen. Matrix-Structural Learning (MSL) of Cascaded Classifier from Enormous Training Set. IEEE International Conference on Computer Vision and Pattern Recognition, 2007 (40 citations by Google Scholar) (CVPR) (国际顶级会议)

[29] J. Chen, V. Kellokumpu, G. Zhao, M. Pietikäinen, RLBP: robust local binary pattern, British machine vision conference, 2013 (90 citations by Google Scholar) (BMVC) (国际顶级会议)

[30] Zhongyi Huang, Yao Ding, Guoli Song, Lin Wang, Ruizhe Geng, Hongliang He, Shan Du, Xia Liu, Yonghong Tian, Yongsheng Liang, S. Kevin Zhou, and Jie Chen; BCData: A Large-Scale Dataset and Benchmark for Cell Detection and CountingMedical Image Computing and Computer Assisted Intervention Society MICCAI 2020, (国际顶级会议)

学生情况(包含协助培养)

博士后:

已出站:高志强 (商汤上海)

在站: 王振楠

博士:

已毕业:郭以沫(美国西门子),李小白(芬兰),柯炜(西安交通大学),刘晴(中南大学),刘娜(天津理工大学),杨博宇(华为),王瑞平(中科院计算所)

在读: 何红亮(国家奖学金),严蕴瑶,乔鹏冲,曾志勇,成泽森,聂志伟,程梦钧

硕士:

已毕业:

2017级:黄伦(美国杜克大学,北京大学优秀毕业生,北京市优秀毕业生),夏雅娴(阿里巴巴),吴倩(网易)

2018级:耿睿哲(bilibili),黄钟毅(腾讯)

2019级:张弛(腾讯),王书博(阿里巴巴),孔子尚,王林(微软),任前,张威风(腾讯) ,张翀(京东),朱丽雯(腾讯),康照东(百度)

在读

2020级:苏晨,任妍,傅滨,韦植丹,黄锦发,程梦钧,程亚璐,张济凡

2021级:李昊,金鹏,喻润一,孙雨菁,李珂涵,冷焯

2022级:张一涵,李世昱,马千坤,王宇,张祎坤,王珺

实习生:

陈麓洋,明原广(Google),Connie Jiang(MIT)


对计划招收的硕士和博士研究生的基本要求

  • 专业范围:计算机科学技术、软件工程、通信工程、电子工程、应用数学、医学、其他相关学科;

  • 外语/数学能力:英语六级;

  • 研究/开发能力:动手能力强,具有合作精神,探索能力和创新精神;

  • 希望学生:有目标、有规划、有内驱力;心中有火,眼中有光

  • 其他能力:有志于科研,抗压能力强,愿意按较高标准严格要求自己。

  • 详细的招生说明见这里