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Yijie Mao
Assistant Professor
Graduated School: University of Hong Kong
Tel: 021-20684454
Office: Room 3-302I, SIST Building
Homepage: http://faculty.sist.shanghaitech.edu.cn/faculty/maoyj
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Research Area: Wireless Communications；Artifical Intelligence-empowered Wireless Networks；Optimization Theory
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Yijie (Lina) Mao is an Assistant Professor at the School of Information Science and Technology, ShanghaiTech University, Shanghai, China. She received the B.Eng. degree from the Beijing University of Posts and Telecommunications, and the B.Eng. (Hons.) degree from the Queen Mary University of London (London, United Kingdom) in 2014. She received the Ph.D. degree in the Electrical and Electronic Engineering Department from the University of Hong Kong (Hong Kong, China) in 2018. She was a Postdoctoral Research Fellow at the University of Hong Kong (Hong Kong, China) from Oct. 2018 to Jul. 2019 and a postdoctoral research associate with the Communications and Signal Processing Group (CSP), Department of the Electrical and Electronic Engineering at the Imperial College London (London, United Kingdom) from Aug. 2019 to Jul. 2021. Her research interests include the design of future wireless communications and artificial intelligence-empowered wireless networks. She is a senior member of China Institute of Communications.

Dr. Mao receives the Best Paper Award of EURASIP Journal on Wireless Communications and Networking 2022 and the Exemplary Reviewer for IEEE Transactions on Communications 2021. She is currently serving as a guest editor for special issues of IEEE Journal on Selected Areas in Communications and IEEE Open Journal of the Communications Society. She has been a workshop co-chair for 2020-2022 IEEE ICC, 2021-2022 IEEE WCNC, and 2020 IEEE PIMRC, and she has been a Technical Program Committee (TPC) member of many symposia on wireless communication for several leading international IEEE conferences.


  • Name：Yijie (Lina) Mao
    Position：Assistant Professor
    Duration：
    Email：maoyj@shanghaitech.edu.cn
  • Name：Tianyu Fang
    Position：Master Student
    Duration：2020 class
    Email：fangty@shanghaitech.edu.cn
  • Name：Xiaohua Zhou
    Position：Master Student
    Duration：2021 class
    Email：zhouxh3@shanghaitech.edu.cn
  • Name：Chengzhong Tian
    Position：Master Student
    Duration：2021 class
    Email：tianchzh@shanghaitech.edu.cn
  • Name：Kangchun Zhao
    Position：Master Student
    Duration：2022 class
    Email：zhaokch12022@shanghaitech.edu.cn
  • Name：Yiwen Wang
    Position：Master Student
    Duration：2022 class
    Email：wangyw22022@shanghaitech.edu.cn
  • Name：Facheng Luo
    Position：Master Student
    Duration：2022 class
    Email：luofch2022@shanghaitech.edu.cn
  • Name：Kexin Chen
    Position：Master Student
    Duration：2023 class
    Email：
  • Name：Haitian Yang
    Position：Master Student
    Duration：2023 class
    Email：

Our research lab, named Future Intelligent Network and Communications (FineCom) Laboratory, is established by Dr. Yijie (Lina) Mao in September, 2021. We mainly focus on the research field of wireless communication networks with emphasis on the potential key technologies for beyond 5G. Our research interests include (but not limited to):

  • MIMO communication systems
    Transceiver design, multi-user interference management, resource allocation.

  • Rate-splitting multiple access (RSMA)
    The theory, architectures, and applications of RSMA.

  • Artificial Intelligence-empowered wireless communication networks (AI + 6G)
    The use of machine learning and deep learning to design efficient algorithms for resource allocation in wireless networks.
    The use of wireless strategies for distributed learning and federated learning.

  • Reconfigurable Intelligent Surface (RIS)
    Phase-shift design, beamforming design, and channel estimation for RIS-aided wireless networks.
    The interplay of RIS with emerging 6G strategies.

  • Space-Air-Ground Integrated Network (SAGIN)
    Interference management, user scheduling, and cooperative transmission design.



CS287: Network Intelligence (Spring, 2022; Autumn, 2022)

Course Introduction

Recent advances in artificial intelligence (AI) and machine learning (ML) has opened a new era of “intelligent wireless networks”, which pushes forward the use of AI technologies to resolve the challenges such as network planning, operation, management and troubleshooting in wireless networks. The development of intelligent wireless networks has been growing explosively and is becoming one of the biggest trends in related academic, research, and industry communities. This course is designed for postgraduate students who are working on the frontiers of wireless communication networks. This course aims at delivering a comprehensive overview of ML, and its application to deal with various problems in the physical (PHY) and medium access control (MAC) layers of communication networks such as transceiver design, channel estimation, prediction, and compression, resource allocation, semantic communications, distributed and federated learning and communications, etc.


EE150: Signals and Systems (Spring, 2023)


Research Service

Editors

Chairs

  • IEEE International Conference on Communications (ICC) 2021 Workshop on Rate-Splitting (Multiple Access) for 6G (co-chaired with Prof. Bruno Clerckx, Prof. Mérouane Debbah, Prof. Daniel B. da Costa, Dr. Peiying Zhu).

Tutorials and Talks

  • I delivered a tutorial on Rate Splitting Multiple Access for 6G in ISWCS 2021, Berlin, Germany (together with Prof. Bruno Clerckx and Dr. Onur Dizdar). [slides]

  • I am invited by Prof. Ruhui Ma to give a talk on Rate Splitting in Shanghai Jiao Tong University.

Technical Program Committee

  • IEEE ICC 2023

  • IEEE WCNC 2023

  • IEEE Globecom 2022

  • IEEE ICC 2022

  • IEEE WCNC 2022

  • IEEE Globecom 2021

  • IEEE ICC 2021

  • IEEE WCNC 2021

  • IEEE ICC 2020

  • IEEE PIMRC 2020






Book Chapter

Y. Mao, B. Clerckx, Multiple Access Techniques, in In: X. Lin, N. Lee (eds) 5G and Beyond , Springer, Cham.