Guowen Xu | Commputer Security | Best Researcher Award

Prof. Guowen Xu, Commputer Security,  Best Researcher Award


Professor at University of Electronic Science and Technology of China, China

Prof. Guowen Xu is a renowned expert in cyberspace security, currently serving as a Professor at the School of Computer Science and Engineering at the University of Electronic Science and Technology of China (UESTC). He holds a Ph.D. in Cyberspace Security from UESTC, where he was supervised by IEEE Fellow Prof. Hongwei Li. He also completed a visiting Ph.D. program at Singapore Management University under the guidance of IEEE Fellow Prof. Robert H. Deng. Prof. Xu has held research fellow positions at Nanyang Technological University and postdoctoral positions at City University of Hong Kong, where he worked with IEEE Fellow Prof. Yuguang Fang. His research interests include applied cryptography, computer security, and AI security and privacy. He has received numerous accolades for his work, including being named one of the Stanford World’s Top 2% Scientists in 2023 and winning several best paper awards at prestigious conferences. Prof. Xu’s contributions to the field have been recognized internationally, and he continues to influence the development of advanced security technologies.

Profile:

Education:

Ph.D. in Cyberspace Security (2015/09 – 2020/12)

  • School of Computer Science and Engineering, UESTC
  • Supervisor: Prof. Hongwei Li (IEEE Fellow)

Visiting Ph.D. in Cyberspace Security (2019/08 – 2020/08)

  • School of Information Systems, Singapore Management University
  • Supervisor: Prof. Robert H. Deng (IEEE Fellow)

Bachelor of Information and Computing Science (2010/09 – 2014/06)

  • School of Mathematical and Physical Science, Anhui Jianzhu University (AHJZU)

Professional Experience:

Prof. Guowen Xu has a distinguished professional background in the field of cyberspace security. He is currently a Professor at the School of Computer Science and Engineering at the University of Electronic Science and Technology of China (UESTC), a position he has held since October 2024. Prior to this, he served as a Postdoctoral Fellow at the Department of Computer Science at City University of Hong Kong from May 2023 to October 2024, where he worked under the supervision of IEEE Fellow Prof. Yuguang Fang. Before his postdoctoral fellowship, Prof. Xu was a Research Fellow at the School of Computer Science and Engineering at Nanyang Technological University in Singapore from March 2021 to May 2023. His early academic career includes a visiting Ph.D. program at Singapore Management University from August 2019 to August 2020, supervised by IEEE Fellow Prof. Robert H. Deng. Prof. Xu’s extensive research experience and collaborations with leading scholars have significantly contributed to his expertise in applied cryptography, computer security, and AI security and privacy.

Research Interest:

Prof. Guowen Xu’s research interests are centered around the fields of applied cryptography, computer security, and AI security and privacy. His work focuses on developing innovative cryptographic techniques to enhance data security and privacy, particularly in the context of complex and evolving cyber threats. In the realm of computer security, he explores robust mechanisms to safeguard systems and networks from vulnerabilities and attacks. Additionally, Prof. Xu is deeply invested in the security and privacy aspects of artificial intelligence, investigating methods to protect AI systems from adversarial threats and ensure the ethical use of AI technologies. His interdisciplinary approach aims to address the pressing security challenges of the digital age, contributing to the advancement of safer and more resilient technological environments.

Awards and Honors:

  • 2023 Stanford World’s Top 2% Scientists
  • 2023 IEEE BigDataSecurity Best Paper Award
  • 2022-2024 Distinguished Reviewer of ACM Transactions on the Web
  • 2022 ECCV Online Registration Waiver Award
  • 2021 Wu Wenjun First Prize of Artificial Intelligence Science and Technology Progress
  • 2021 Outstanding Graduate Student of UESTC
  • 2021 Outstanding Graduate Student in Sichuan Province
  • 2021 IEEE INFOCOM Student Conference Award
  • 2020 IEEE ICPADS Best Paper Award
  • 2020 National Scholarship of Graduate Student (MOE of PRC, Top 1%)
  • 2020 First-class Scholarship of Graduate Student (UESTC, Top 1%)
  • 2019 SCF Best Student Paper Award (Sichuan Province Computer Federation)
  • 2019 National Scholarship of Graduate Student (MOE of PRC, Top 1%)
  • 2019 First-class Scholarship of Graduate Student (UESTC, Top 1%)
  • 2018 Network Security Scholarship of China Internet Development Foundation
  • 2018 National Scholarship of Graduate Student (MOE of PRC, Top 1%)
  • 2018 First-class Scholarship of Graduate Student (UESTC, Top 1%)
  • 2018 First-class Scholarship of Shenzhen Huiding Technology Co., Ltd (Top 1%)
  • 2018-2020 Excellent Student Award (UESTC)
  • 2018-2020 Excellent Graduate Student (UESTC)
  • 2016 Excellence Award of National Cipher Technology Competition

Publication Top Noted:

VerifyNet: Secure and Verifiable Federated Learning

  • Authors: G. Xu, H. Li, S. Liu, K. Yang, X. Lin
  • Journal: IEEE Transactions on Information Forensics and Security
  • Volume: 15
  • Pages: 911-926
  • Citations: 570
  • Year: 2020

Efficient and Privacy-Enhanced Federated Learning for Industrial Artificial Intelligence

  • Authors: M. Hao, H. Li, X. Luo, G. Xu, H. Yang, S. Liu
  • Journal: IEEE Transactions on Industrial Informatics
  • Volume: 16
  • Issue: 10
  • Pages: 6532-6542
  • Citations: 472
  • Year: 2019

Enabling Efficient and Geometric Range Query with Access Control over Encrypted Spatial Data

  • Authors: G. Xu, H. Li, Y. Dai, K. Yang, X. Lin
  • Journal: IEEE Transactions on Information Forensics and Security
  • Volume: 14
  • Issue: 4
  • Pages: 870-885
  • Citations: 192
  • Year: 2018

Towards Efficient and Privacy-Preserving Federated Deep Learning

  • Authors: M. Hao, H. Li, G. Xu, S. Liu, H. Yang
  • Conference: ICC 2019 – IEEE International Conference on Communications
  • Pages: 1-6
  • Citations: 178
  • Year: 2019

Privacy-Enhanced Federated Learning against Poisoning Adversaries

  • Authors: X. Liu, H. Li, G. Xu, Z. Chen, X. Huang, R. Lu
  • Journal: IEEE Transactions on Information Forensics and Security
  • Citations: 158
  • Year: 2021