Yuzhou Fang

Yuzhou Fang

Research Assistant

The Chinese Univesity of Hong Kong


My name is Yuzhou Fang (方钰舟). I am currently a Research Assistant (expected from Oct. 2021 to Sept. 2022) at the Department of Information Engineering, the Chinese University of Hong Kong, supervised by Prof. Wu, Daoyuan. I received my B.E. in Cybersecurity from Shcool of Cybersecurity, Sichuan University.

My research interests currently include detecting vulnerabilities via program analysis techniques and other interesting topics about security.

During my undergraduate, I worked on detecting spammer bots in Sina Weibo by leveraging Deep Learning-based approaches with Prof. Wang, Haizhou. Now, with Prof. Wu, Daoyuan, I’m trying to find the vulnerabilities in both Blockchain systems (e.g., Bitcoin-core) and smart contracts. We have detected a few cloned vulnerabilities in the top Bitcoin forked projects (see details in Forked-Chains).

I also have great interests in other security things, such as CTF challenges and cool hacking skills. In 2022, I plan to do my Ph.D. applications after finishing my RA. Good luck to myself!

Click here to download my resumé.

  • Software Security
  • Program Analysis
  • Blockchain Security
  • B.E. in Cybersecurity, 2021

    Sichuan University


The Chinese University of Hong Kong
Research Assistant
Oct 2021 – Jul 2022 Hong Kong
Advised by Prof. Wu, Daoyuan, mainly focused on detecting vulnerabilities in Blockchain systems and smart contracts.
National University of Singapore
Undergraduate Visiting Student
Jul 2020 – Aug 2020 Signapore
Participated in the NUS SOC 2019 Summer Workshop. Majored in the course of Defense of the Ancients (”DOTA”).
Sichuan University
Undergraduate Student
Sep 2017 – Jun 2021 China
Undergraduate student advised by Prof. Wang, Haizhou, mainly focused on social spammer detection.


(2022). An Empirical Study of Blockchain System Vulnerabilities: Modules, Types, and Patterns. In ESEC/FSE.


(2021). A novel framework for detecting social bots with deep neural networks and active learning. In KBS.


(2020). Detecting Social Spammers in Sina Weibo Using Extreme Deep Factorization Machine. In WISE.




  • yzfang98[at]gmail.com
  • 826B, Ho San-Hang Engineering Building, CUHK, Hong Kong SAR,
  • DM Me