Yujia Zhu
Exeter,Devon
Summary
Computational researcher in systems reliability and machine learning. My PhD in the UK (thesis submitted; minor corrections anticipated) develops log-based anomaly detection and root-cause localisation with reproducible pipelines and open-source code. Skilled in Python (PyTorch/Keras, Scikit-learn, Pandas) and C/C++, with strong data processing, evaluation, and Git/GitHub practices. Familiar with NLP/LLMs and prompt design. A resilient, collaborative teammate who learns new tools fast and delivers careful, well-documented experiments.
Overview
7
7
years of professional experience
Work history
Data Study Group
Alan Turing Institute
Exeter, Devon
08.2023 - 09.2023
- Conducted comprehensive data analysis, aiding decision-making process.
- Streamlined data analysis processes for more efficient campaign monitoring.
- Developed algorithms for data analysis, improving business intelligence.
- Utilised statistical software for detailed data analysis, improving research outcomes.
Teaching Assistant
University of Exeter
Exeter, Devon
09.2018 - 12.2018
- Assisted Dr. Lorenzo Livi with the module "Learning From Data" in teaching and administrative duties for the course.
• Graded assignments and provided constructive feedback to students.
• Organised and conducted tutorial sessions and workshops, enhancing students' understanding of the course material.
Software engineering intern
China Telecom Nanchong Branch
Nanchong, Sichuan
06.2016 - 09.2016
- Involved in regular code review sessions to ensure quality output and conformity to company standards.
- Researched new technologies to keep up-to-date with industry trends and advancements,.
- Assisted in the creation of technical documentation to streamline future projects.
- Conducted software testing, enhanced performance reliability.
Education
Bachelor of Engineering - Electronic Engineering
Wuhan University
Wuhan, China 09.2012 - 06.2016
Doctor of Philosophy - Computer Science
University of Exeter
Exeter 09.2016 -
Skills
Programming: Python (NumPy, pandas, scikit-learn, PyTorch, Keras), MATLAB, C/C, C, Bash; Git/GitHub, Linux
ML/AI: deep learning, representation learning, anomaly detection, sequence modelling (LSTM/Transformer), experiment design & reproducibility
NLP/LLMs: transformers, prompt engineering & evaluation, familiar with fine-tuning and RAG; Hugging Face tools
Systems & Data: log parsing and template mining, root-cause localisation, data cleaning, feature engineering, analysis & visualisation
Algorithms: strong data structures & algorithms; competitive problem-solving mindset
Hardware/Embedded: microcontrollers, digital circuits; assembly, basic HDL (Verilog/VHDL)
Networks: fundamentals of computer networking and protocols
Professional: resilient, quick learner, collaborative; positive feedback from supervisors and peers
Publications
- Zhu, Yujia, Yulei Wu, Geyong Min, Albert Zomaya, and Fei Hu. "A survey of big data and computational intelligence in networking." In Big Data and Computational Intelligence in Networking, pp. 3-26. CRC Press, 2017.
- Zhu, Yujia, Geyong Min, Yulei Wu, and Haozhe Wang. "Automatic Anomaly Detection Using Unlabelled Log Data." In 2023 IEEE International Conference on High Performance Computing & Communications, Data Science & Systems, Smart City & Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys), pp. 507-514. IEEE, 2023.
- Zhu, Yujia, Geyong Min, Yulei Wu, and Haozhe Wang. "Automated Log-Based Anomaly Detection under Noise Circumstances." In 2023 IEEE Smart World Congress (SWC), pp. 822-827. IEEE, 2023.
- Zhu, Yujia, Geyong Min, Yulei Wu, and Haozhe Wang. "A Time Series Clustering Method for Network Big Data." In 2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS), pp. 1516-1521. IEEE, 2023.
Accomplishments
- National Scholarship (Ministry of Education, China), Wuhan University, 2013 and 2014
- Outstanding Graduate, Class of 2012, Wuhan University
- Outstanding Organiser, IEEE HPCC 2018 — Local Organising Committee Member
Academic Service & Leadership
- Reviewer, Big Data Mining and Analytics (BDMA), 2023
- Local Organising Committee, IEEE International Conference on High Performance Computing and Communications (HPCC) 2018 — Outstanding Organiser Award
- Web & System Management Co-Chair, 13th IEEE International Symposium on Social Computing and Networking (SocialCom 2020), Exeter, UK, 15–17 Oct 2020 (held virtually due to COVID-19)
Languages
English
Proficient (C2)
Mandarin
Native
References
- Prof. Geyong Min
- Chair in High Performance Computing and Networking, University of Exeter
- Email: G.Min@exeter.ac.uk
Timeline
Data Study Group
Alan Turing Institute
08.2023 - 09.2023
Teaching Assistant
University of Exeter
09.2018 - 12.2018
Doctor of Philosophy - Computer Science
University of Exeter
09.2016 -
Software engineering intern
China Telecom Nanchong Branch
06.2016 - 09.2016
Bachelor of Engineering - Electronic Engineering
Wuhan University
09.2012 - 06.2016
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