PhD Student at School of Computing Newcastle University
R.Xue5 [at] newcastle.ac.uk
github: https://github.com/firepond
I build resource-efficient and secure intelligence for the Internet of Things. My research connects streaming anomaly detection, TinyML, and lifelong learning so embedded devices can adapt on the edge without sacrificing reliability.
Research Focus
- IoT intelligence and security for cyber-physical systems
- Streaming anomaly detection and change point analysis
- Tiny machine learning for constrained devices
- Lifelong and continual learning pipelines
- Autonomous agents applied to embedded sensing
Education
Newcastle University, United Kingdom
PhD in Computing, 2024 - present
Focus on IoT intelligence, TinyML, anomaly detection, and agent-driven automation.
University of Glasgow, United Kingdom
MSc in Computer Systems Engineering, Sept 2022 - Oct 2023
- Graduated with Distinction; GPA 17.8/22
Beihang University (BUAA), Beijing, China
Bachelor of Engineering in Information Security, Sept 2017 - Sept 2021
- Graduated with Honors from ShenYuan Honors College
Publications
- STREAM-LAD: A Practical Streaming Lifelong Anomaly Detection Algorithm for IoT. ICDM OWAD, 2025.
- Energy-Efficient Change Point Detection Algorithm for Resource-Constrained Devices. EWSN EMERGE Workshop, 2025.
Selected Skills
- Programming: Java, Python (PyTorch, NumPy, scikit-learn), C and C++, CUDA, Go, SQL
- Embedded systems: Raspberry Pi, ESP32, Arduino; high level and low level development
- Tooling: Linux (Kali, Ubuntu), Bash and Zsh scripting, LaTeX (Overleaf), Microsoft Office, Git
Languages
- English: Professional proficiency (TOEFL 103)
- Chinese: Native
- Japanese: A2
If you would like to collaborate on IoT intelligence or TinyML research, please get in touch.