Research Focus
  • Next-generation Private Network Technology

Research in this area focuses on the R&D and innovations of the 5G/6G mobile communications system in the industrial private network field. In line with the needs of industrial customers, the XG Lab has developed technologies in fields such as communications protocols, AI, and the integration of networks and cloud services. The XG Lab works closely with ecosystem partners and delivers key technological innovations for clouds, networks, edges, and devices. The research aims to build maintenance-free, low-cost, and easily iterated industrial private networks and develop digital intelligence technologies that are fundamental to digital transformations in all industries.

  • Mobile Network Transmission Technology

Research in this area focuses on the optimization of high-performance streaming media transmission protocols for 5G and next-generation mobile networks. The research aims to resolve packet loss and transmission latency issues and improve the user experience of streaming data transmission over mobile networks. The research covers fields such as mobile network visualization, multipath scheduling, lightweight network encoding, and QoE-driven network congestion control.

  • Video Encoding and Decoding Technology

Research in this area focuses on the development of cutting-edge video encoding and decoding technologies for 5G and next-generation networks. The research aims to achieve narrowband HD and broadband UHD, which will significantly boost the development of video applications. The XG Lab develops technologies and products related to UHD videos, immersive videos, and real-time rendering on the cloud, and empowers new applications. It also develops the video encoding and decoding technology based on deep learning, and plays a leading role in the formulation of international and Chinese video-specific standards.

  • 5G Application Technology

Research in this area focuses on developing innovative application technologies for 5G. 5G delivers high-bandwidth, low-latency connectivity and promises the collaboration of clouds, networks, edges, and devices. The research aims to make innovations in application and network systems and develop real-time rendering on the cloud, real-time 3D modeling, AR/VR, and UHD immersive video products and services. The research contributes to better user experiences of devices and gives birth to new applications and values for 5G.

Research Team
Ming ZhangDirector of XG Lab

Ming Zhang holds a PhD in computer science from Princeton University, USA. His research interests include 5G, edge networks, cloud data center networks, and backbone networks. Before joining Alibaba, he was a senior researcher of Microsoft Research Asia and responsible for research on key cloud networking technologies of Microsoft Azure. He published many forward-looking and influential papers in world-class academic conferences and journals, and was invited to serve as a reviewer at world-class academic conferences (such as ACM SIGCOMM).

Yan YeLeader of Video Technology Team at XG Lab

Yan Ye holds a PhD from the University of California, San Diego, and bachelor's and master's from University of Science and Technology of China. She is dedicated to the research of cutting-edge video compression and processing technologies and the development of international video standards. Her experience spans three generations of international video standards including H.264/AVC, H.265/HEVC, and H.266/VVC. She also was/is an editor of MPEG LCEVC, H.265/HEVC, H.266/VVC test model, and 360Lib algorithm description.. She chairs the INCITS L3.1 and the ISO/IEC/SG29/AG5 360 video group. She is a guest editor of IEEE TCSVT and serves on many IEEE top conference program committees (such as DCC, VCIP, PCS, ICME, and ICIP). She is an inventor of more than 260 US patents and an author of more than 50 peer-reviewed articles. She is an IEEE senior member. She has been invited to write numerous articles and give many talks on VVC and HEVC.

Guang YangChief Network Architect at XG Lab

Guang Yang holds a PhD from Beijing University of Posts and Telecommunications and is a professorate senior engineer. His research focuses on mobile communications. Before joining Alibaba, he served China Mobile Research Institute and was responsible for technical standard formulation, industry construction and promotion, large-scale testing and commercial deployment, and global promotion in projects such as LTE TDD (4G), NB-IoT, 5G, and joint innovations for the vertical industry. He has served as a reporter of many 3GPP standards, holds more than 50 patents, and has published 5 monographs. He has won many provincial science progress awards. In 2016, he won the National Science Progress Award (Special Class) by virtue of the LTE TDD project.

Hongqiang LiuLeader of Network Transmission Technology Team at XG Lab

Hongqiang Liu holds a PhD from the Department of Computer Science at Yale University and a bachelor's degree and a master's degree from the Department of Electronic Engineering at Tsinghua University. Before joining Alibaba, he served as a researcher at Microsoft Research Asia and was responsible for the R&D and implementation of key technologies related to stable, high-performance Azure networks. His research interests cover cloud data center networks, backbone networks, mobile network transmission technologies, 5G networks, and device-side computing. He has served as a reviewer of papers in SIGCOMM and NSDI conferences and has published nearly 20 papers accepted by SIGCOMM, NSDI, and SOSP conferences. In 2014, he won the SIGCOMM Doctoral Dissertation Award - Honorable Mention.

Academic Achievements
  • Y. Ye, J. Boyce, P. Hanhart, Omnidirectional 360° Video Coding Technology in Responses to the Joint Call for Proposals on Video Compression With Capability Beyond HEVC, IEEE Transactions on Circuit and Systems for Video Technology, special section on the joint Call for Proposals on video compression with capability beyond HEVC, Volume: 30, Issue: 5, pp. 1241-1252, May 2020.
  • H. Gao, R.-L. Liao, K. Reuz, S. Esenlik, E. Alshina, Y. Ye, J. Chen, J. Luo, C.-C. Chen, H. Huang, W.-J. Chien, V. Seregin, M. Karczewicz, Advanced Geometric-based Inter Prediction for Versatile Video Coding, IEEE Data Compression Conference (DCC), 2020.
  • T. Lu, F. Pu, P. Yin, S. McCarthy, W. Husak, T. Chen, E. Francois, C. Chevance, F. Hiron, J. Chen, R.-L. Liao, Y. Ye, J. Luo, Luma Mapping with Chroma Scaling in Versatile Video Coding, IEEE Data Compression Conference (DCC), 2020.

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