Shiguang Shan received M.S. degree in computer science from the Harbin Institute of Technology, Harbin, China, in 1999, and Ph.D. degree in computer science from the Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS), Beijing, China, in 2004. He joined ICT, CAS in 2002 and became a full Professor in 2010. He is now the director of the Key Lab of Intelligent Information Processing of CAS.
His research interests cover computer vision, pattern recognition, and machine learning. He especially focuses on computational face perception related research topics, and machine learning with data of limited supervision. He has published more than 300 papers in refereed journals and proceedings. He has served as Area Chair (or Senior PC) for many international conferences including CVPR19/20/21/22, AAAI20/21/22, IJCAI21, ICPR12/14/20, ACCV12/16/18, FG13/18/20, BTAS18, ICASSP14, and ICCV11. He is(/was) Associate Editors of several international journals including IEEE Trans. on Image Processing, Computer Vision and Image Understanding, Neurocomputing, and Pattern Recognition Letters. He is a recipient of the China’s State Natural Science Award in 2015, and the China’s State S&T Progress Award in 2005 for his research work.
He is also the co-founder and rotating Chairman of Steering Committee of VALSE (Vision And Learning SEminar), a China-based non-official scholarly community. VALSE holds annual conference every year since 2011, and has held more than 220 times of Webinar (online seminar) since 2014. Numerous Chinese researchers and students have benefitted from these VALSE events. Taking VALSE Annual Conference 2019 as an example, more than 5,000 audiences attended this event held in Hefei China.
He is also personally interested in brain science, cognitive neuroscience, as well as their interdisciplinary researche topics with AI.
My ORCID: https://orcid.org/0000-0002-8348-392X
My Google scholar: https://scholar.google.com/citations?user=Vkzd7MIAAAAJ
山世光，中科院计算所研究员、博导，现任中科院智能信息处理重点实验室主任。他的研究领域为计算机视觉和机器学习。已在国内外刊物和学术会议上发表论文300余篇，其中CCF A类论文100余篇，论文被谷歌学术引用25,000余次。所研发的人脸识别相关研究成果获2005年度国家科技进步二等奖，在高维、非线性视觉模式分析方面的研究成果获2015年度国家自然科学二等奖。他带领团队研发的人脸识别技术已应用于公安部门、华为等众多产品或系统中，取得了良好的经济和社会效益。曾应邀担任过ICCV11，ACCV12/16/18，ICPR12/14/20，FG13/18/20，ICASSP14，BTAS18, AAAI20/21/22, IJCAI21, CVPR19/20/21/22等十余次领域主流国际会议的领域主席，现/曾任IEEE TIP, CVIU, PRL, Neurocomputing, FCS等国际学术刊物的编委(AE)。他是基金委优青，国家重要人才计划入选者，科技部创新人才推进计划中青年科技创新领军人才，人社部国家百千万人才工程有突出贡献中青年专家，CCF青年科学家奖获得者，北京市科技新星，中科院青促会优秀会员。
 Associate Editor of Frontier of Computer Science (2018-)
 Associate Editor of IEEE Trans. on Image Processing (2015-2018)
 Associate Editor of Journal of Computer Vision and Image Understanding (2017-)
 Associate Editor of Pattern Recognition Letters (2017-)
 Associate Editor of Neurocomputing (2012-2016)
 Editor Board member of EURASIP Journal of Image and Video Processing
 Associate Editor of IPSJ Transactions on Computer Vision and Applications (CVA)
 Associate Editor of IET Computer Vision (2020-)
 General Co-chair of IEEE Conference on Face and Gesture Recognition 2023 (FG2023)
 General Co-chair of Asian Conference on Computer Vision (ACCV) 2022
 Area Chair of the 36th AAAI Conference on Artificial Intelligence (AAAI2022)
 Area Chair of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21)
 Area Chair of the 35th AAAI Conference on Artificial Intelligence (AAAI2021)
 Area Chair of IEEE/CVF Conference on Computer Vision and Pattern Recognition 2021
 Area Chair of IEEE Conference on Face and Gesture Recognition 2020 (FG2020)
 Senior PC of the 34th AAAI Conference on Artificial Intelligence (AAAI-20)
 Area Chair of IEEE/CVF Conference on Computer Vision and Pattern Recognition 2020
 Area Chair of IEEE/CVF Conference on Computer Vision and Pattern Recognition 2019
 Area Chair of IEEE International Conference on Biometrics: Theory, Application AND Systems (BTAS 2018)
 Area Chair of IEEE International Conference on Automatic Face and Gesture Recognition (FG 2018)
 Area Chair of Asian Conference on Computer Vision (ACCV) 2018
 Area Chair of International Conference on Computer Vision (ICCV) 2011
 Program Chair of Chinese Conference on Biometric Recognition 2014, 2015, 2016
 Area Chair of International Conference on Pattern Recognition (ICPR) 2012
 Area Chair of Asian Conference on Computer Vision (ACCV) 2012
 Area Chair of International Conference on Face and Gesture Recognition (FG2013)
 Workshop Chair of Asian Conference on Computer Vision (ACCV) 2014
 Area Chair of Asian Conference on Computer Vision (ACCV) 2016
 Area Chair of International Conference on Pattern Recognition (ICPR) 2014
1. Machine learning: deep learning and beyond
My team focuses on new machine learning methods for scenarios with complex data conditions, especially small data, wealy-labeled data, semi-supervised data, incomplete data, where new models and new optimizing methodsareneeded to design. In terms of methodology, I am interested in self-supervised learning, transfer learning, meta-learning, and knowledge-guided learning.
2. From face recognition to deep human understanding: methods, technologies, and applications
My team is interested in all kinds of vision tasks from face recognition to human understanding, including (but not limited to) face detection and tracking, facial landmark locating, face alignment, face identification, face verification, face retrieval, expression recognition, facial attribute estimation, 3D face reconstruction, face parsing, lip reading, heart rate estimation, engagement estimation, gaze tracking, etc. We have broad cooperation with industrial parters, including Huawei, Ping'an, Qualcomm, China Mobile, Baidu, Isvision, Samsung, Omron, Panasonic, etc. Especially, our face recognition technology has been used on Huawei smart phone and Huawei Cloud album.
3. Generic object detection, segmentation, and recognition
My team is also interested in generic object detection, segmentation, and recognition, especially pedestrian detection and tracking, human pose estimation and body segmentation, vehicle detection and tracking, human and vehicle re-identification etc. These technologies are applied to video surveillance.
1. Please kindly refer to my Google scholar homepage： https://scholar.google.com/citations?user=Vkzd7MIAAAAJ&hl=zh-CN