😀 About me

I specialize in WiFi localization, leveraging deep learning techniques to address challenges in indoor positioning.

🔥 News

  • Mar 2025: Oh, I was just rejected by TMC. Haha. See you next time!

  • Dec 2024: This year, I have dedicated substantial time to exploring a new platform, tackling a variety of engineering challenges 😓. The exciting news is that a paper based on this platform has just been submitted to TMC—stay tuned for more updates! 🎉

  • Oct 2024: I was delighted to meet everyone in Melbourne. Looking forward to our next gathering!

📑 Publications

Indoor Localization · CSI · Angle of Arrival

Leveraging uncertainty quantification to improve the robustness and accuracy of angle-based methods.

Indoor Localization · ISAC · Data-driven · Large-scale

Exploring data-driven localization on a large-scale ISAC platform.

More results coming soon …

💻 Projects

  • Human-held device WiFi indoor localization dataset: We have developed the H-WILD dataset for WiFi-based indoor localization using human-held devices. Special thanks to my collaborator, Guanzhong Wang. I welcome potential collaborations to enhance the value of this project for the community.

🏆 Honors and Awards

  • Nov 2023: Awarded Second Prize (2nd out of 287 teams) and 100,000 CNY in the First WiFi Sensing Contest as the team leader. I am grateful to my partner for their collaboration and support, and I extend special thanks to Tongzhou Zhou for his invaluable guidance on my presentation.

  • Undergraduate:

    • Awarded the People’s First-Class Scholarship (GPA: 3.8/4.0)
    • Secured first prizes in both national and intra-university competitions
    • Recognized as a Merit Student and received the Excellent Student Cadre Award

📖 Educations

2023 - Present

Ph.D. in Cyberspace Security

University of Science and Technology of China

2021 - 2023

M.S. in Computer Technology

University of Science and Technology of China

2017 - 2021

B.S. in Automation

University of Science and Technology of Beijing

Excellent Engineer Program