Prof. Yang Can

Can Yang (Member, IEEE) received the B.S. degree in Electronic Science and Technology from Huazhong University of Science and Technology (HUST), Wuhan, China, in 1994; the M.S. degree in Pattern Recognition and Intelligent Control from the Image Institute in June 1997; and the Ph.D. degree in Electronic Science and Technology from HUST in 2002. He was a Postdoctoral Fellow with the School of Computer Science and Technology, HUST, from August 2002 to October 2004, and a Visiting Scholar with the Department of Electrical and Computer Engineering, New York University, from 2013 to 2014.

He is currently with the School of Computer Science and Engineering, South China University of Technology (SCUT), where he became an Associate Professor in February 2005 and has been a Professor since May 2012. His research interests include artificial intelligence, big data, and cloud-based multimedia networking.

Professor Yang has received multiple awards, including the Guangdong Province Science and Technology Progress Award (2011, 2015), the Science and Technology Innovation Award of the State Administration of Radio and Television (SARFT) of China (2012), and the First-Level Excellent Paper Award of the Guangdong Computer Academy (GDCA) (2021). He is a member of ACM, a Council member of GDCA, and a Senior Member of CCF.

He serves as a graduate supervisor at SCUT, is the Director of the Cloud Intelligent Service / Cloud Media Lab, and is credited with initiating three major technologies: the Cross-Layer Neural Network Net95, the Best Adaptive Network Application Layer Multicast BANACAST, and the General Web Data Intelligence GWDI. He also participated in the development of China’s first digital laser 3D scanner and the XY-20 trajectory planning system. He has led more than 20 national and provincial research projects, as well as commissioned R&D projects from enterprises and institutions.

Professor Yang has published over 80 papers, held over 60 patents (including 35 granted patents and 3 international PCT patents), 11 software copyrights, and has led the drafting of 7 international and domestic standards. He has published over 80 papers in journals and conferences such as IEEE Transactions on Information Forensics and Security, IEEE Transactions on Multimedia, IEEE Transactions on Biometrics, Behavior, and Identity Science, IEEE Transactions on Circuits and Systems for Video Technology, Chinese Journal of Electronics, Journal of Computer Science and Technology, ACM MMSys, and CVPR. He teaches courses including Operating Systems, Software Engineering, Multimedia Communication Technology, Distributed Computing (Principles and Applications), and Network Media. He has supervised more than 100 graduate students, whose achievements include awards such as the Special Prize in the Guangdong Province “Challenge Cup.”

Contact:
Email: cscyang@scut.edu.cn
WeChat: banacast

Research Group/Team Overview — Cloud Intelligent Service Lab

The Cloud Intelligent Service Lab focuses on core theories and key technologies for big-data intelligence, cloud ecosystem service software, and large-scale multimedia communication network applications. Recent research directions include big data, AI, recommendation systems, cloud engineering, P2P networking, coding, IPTV, and live video streaming.

The lab is an interdisciplinary, internationally oriented team initiated by core members from the former Multimedia and Graphics/Image Group (Prof. Guoqiang Han) at SCUT. It has undertaken more than 20 national and provincial major projects as well as international collaboration projects, and participates in national video encoding standardization efforts. The lab also maintains an in-house DevOps platform for software R&D and operations.

The team includes one IEEE Fellow, five professors, and five associate professors, and has trained a large number of graduate and undergraduate students. Its members have published extensively in top venues (e.g., IEEE Transactions, CVPR, InfoCom) and hold numerous invention patents and software copyrights. The lab has contributed to multiple national standards and IETF-related standards, and has published international academic monographs.

Among its notable systems, the BANACAST cloud intelligent adaptive network transmission technology has been applied at large scale, and the lab’s GWDI platform (initiated since 2011) explores early low-code approaches for web-based intelligent model construction and reasoning experimentation. The lab has provided technical services to a wide range of government, healthcare, telecom, broadcasting, and industrial organizations, and continues to pursue open ecosystem research with the goal of advancing big data–driven AI for real-world industries such as telecommunications, broadcasting, power systems, and finance.