Dr. Shengcai Liao

IEEE Fellow, IAPR Fellow, Associate Professor, Director of Computer Vision Lab (CVLab)
College of Information Technology (CIT), United Arab Emirates University (UAEU), Al Ain, UAE
Email: scliao at ieee
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Short Bio

Shengcai Liao is an Associate Professor and founding director of the Computer Vision Lab (CVLab) in the College of Information Technology (CIT) in UAEU. He is an IEEE Fellow and IAPR Fellow. He was a Principal Scientist in IIAI, G42 in UAE during 2018-2024, and an Associate Professor in Institute of Automation, Chinese Academy of Sciences (CASIA) from 2014 to 2018. He received B.S. degree in mathematics from Sun Yat-sen University in 2005 and Ph.D. degree from CASIA in 2010. He was a Postdoc at Michigan State University during 2010-2012. He is interested in face and person detection, recognition, analysis, and image and video generation. He has published 100+ papers, with 23,083 citations and h-index 56. He ranks #905 among 215,114 world-wide AI scientists (Top 0.42%) in 2019 (by Stanford University). His representative work LOMO+XQDA for person re-identification has been cited 2,643 times and ranks #11 in the Most Influential CVPR Papers 2015. He was awarded Best Paper/Best Student Paper in ICB 2006/2007/2015, and CCBR 2016, Best/Outstanding Reviewer in IJCB 2014, CVPR 2019/2021, Great Contribution Award for Beijing 2008 Olympic Games, Second-Class Award of the China State Science and Technology Progress Award 2019, and Winner of CVPR 2017 Detection in Crowded Scenes Challenge and ICCV 2019 NightOwls Pedestrian Detection Challenge. He served as an Assistant Editor for “Encyclopedia of Biometrics, 2nd Ed.”, Guest Associate Editor for IEEE T-BIOM, and Associate Editor for IEEE TIP and TMM. He led a successful bid of hosting IJCB 2022 at Abu Dhabi and served as a Program Chair. He served as Program Chair for ICIG 2025 and Area Chair for ICPR 2016, ICB 2016/2018, CVPR 2022/2023/2025, ICCV 2023/2025, ICML 2025, NeurIPS 2023-2025, ECCV 2024, AAAI 2025, and WACV 2024/2025.

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Research Interests

Computer Vision, Pattern Recognition, Machine Learning

Face Detection, Face Recognition, Biometrics

Object Detection, Object Tracking, Person Re-identification

Similarity/Metric Learning, Deep Learning, Domain Generalization

Multimodal LLM, Image and Video Generation, Embodied AI, and Digital Humans

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