About me

Hi, I am Junyuan Fang (房俊源 in Chinese). I am currently a fourth-year Ph.D. student at City University of Hong Kong (CityU), where I am fortunate to be advised by Prof. C. K. Michael Tse. I received the bachelor’s degree from Guangdong University of Technology (GDUT) in 2018, and master’s degree from Sun Yat-sen University (SYSU) in 2020, advised by Dr. Jiajing Wu and Prof. Zibin Zheng. My research interests are in the area of graph mining. More specifically, I am focused on the area of graph neural networks including their theory foundations, adversarial robustness and applications. I also have a strong passion for the robustness optimization against cascading failures in Cyber-physical systems (CPS).

Email: junyufang2-c [AT] my [DOT] cityu [DOT] edu [DOT] hk

News

• [01/2024] One previous preprint about the imperceptible node injection attacks in graph neural networks has been accepted by TCSS.
• [01/2024] One collaborative paper about the mitigation of cascading failure in power network has been accepted by ISCAS2024.
• [01/2024] One collaborative paper about the detection of phishing gangs in Ethereum has been accepted by TIFS.
• [09/2023] I am honored to be awarded the 2023 Research Tuition Scholarship at CityU.
• [06/2023] One paper about the homophily and heterophily information aggregation for Ethereum account classification has been accepted by JETCAS. [Paper]
• [06/2023] I am honored be selected to receive a 2023 IEEE CASS Student Travel Grant for attending ISCAS2023.
• [01/2023] One paper about the impact of network topologies to the performance of GNNs has been accepted by ISCAS2023. [Paper], [Code]
• [01/2023] I am honored to be selected to attend GYSS2023 virtually.
• [10/2022] New preprint “GANI: Global Attacks on Graph Neural Networks via Imperceptible Node Injections” and corresponding codes are available now. [Paper], [Code]