I am an incoming PhD student in the Computer Science Department
at University of Arizona, advised by Professor Zhuolin Yang.
I received my bachelor degree in Computer Science and Technology at Shanghai University
and my master degree in Security Informatics at Johns Hopkins University.
Before my graduate study, I worked as a cybersecurity engineer in industry,
specializing in security monitoring, security operations and security project management
such as NDR, EDR, SAST and mobile application security.
About
My research interest focuses on physical-layer security, low-level hardware and software security.
I have worked in a counter-drone project where we developed a C-UAV (Counter-Unmanned Aerial Vehicles) platform
to detect and mitigate malicious drones using sensor fusion (RF, camera, acoustic etc.).
I led mitigation testings across different commercial drones, evaluating GPS spoofing,
Wi-Fi deauthentication, optical, infrared, and ultrasonic interference attacks.
I have also involved in a cloud security project that builds
a unified, provider-agnostic abstraction for IAM that connect through AWS, GCP, and Azure.
Beyond computer science, I have deep interests in astronomy, calligraphy, cello, tennis, detective stories, and Sci-Fi. :)
Projects
Current and past projects in security.
Multi-Cloud Security Policy Orchestration: An Abstraction Layer for IAM Management
Developing a unified IAM abstraction layer that integrates IAM components from multi-cloud providers and models them as a graph for intuitive governance. The system supports bidirectional synchronization, static permission mapping, and diff-based updates. The unified IAM data model and normalized permission mapping enable security teams to manage cross-cloud identities through a single, intuitive interface while preserving platform-specific semantics.
Publications
Accepted papers and technical reports.
SICSI '25
Dark Drones: Can They Be Automatically Detected and Mitigated?
First IEEE International Workshop on Secure Industrial Control Systems and Industrial IoT (SICSI'25), co-located with IEEE CNS, 2025.