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Dr. Yishu Li
李一舒 PhD Graduate (2024) 2024Now Lecturer, Department of Electronic Engineering and Computer Science, School of Science and Technology, Hong Kong Metropolitan University, Hong Kong
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Dr. Yishu Li is a PhD graduate in the Department of Computer Science, City University of Hong Kong.
Now Lecturer, Department of Electronic Engineering and Computer Science, School of Science and Technology, Hong Kong Metropolitan University, Hong Kong.
Research Interests
Publications (22)
- Where Do Expectations Diverge? an Empirical Analysis of Software Engineering Graduate Preparedness in Industry.
- UniAda: Universal Adaptive Multi-objective Adversarial Attack for End-to-End Autonomous Driving Systems.
- Teaching Software Engineering with LLM and MCP Integration: From Classroom to Industry Practice.
- R2Code: A Self-Reflective LLM Framework for Requirements-to-Code Traceability.
- NFR-to-Code Traceability in a Blockchain-IoT System: An Empirical Study.
- Designing Psychologically Safe AI Tutors for Students: An Emotion-Aware Post-Hoc Intervention for LLM-Assisted Learning.
- Practitioners' Expectations on Log Anomaly Detection.
- On the Influence of Data Resampling for Deep Learning-Based Log Anomaly Detection: Insights and Recommendations.
- A Comprehensive Study of Bugs in Modern Distributed Deep Learning Systems.
- TerGEC: A graph enhanced contrastive approach for program termination analysis.
- SimAC: simulating agile collaboration to generate acceptance criteria in user story elaboration.
- LLM-Based Class Diagram Derivation from User Stories with Chain-of-Thought Promptings.
- Improving domain-specific neural code generation with few-shot meta-learning.
- Enhancing the Transferability of Adversarial Attacks for End-to-End Autonomous Driving Systems.
- Enhancing Valid Test Input Generation with Distribution Awareness for Deep Neural Networks.
- Agile Requirements Engineering in a Distributed Environment: Experiences from the Software Industry During Unprecedented Global Challenges.
- A Semisupervised Approach for Industrial Anomaly Detection via Self-Adaptive Clustering.
- Integrating Generative AI in Software Engineering Education: Practical Strategies
- Towards Requirements Engineering Activities for Machine Learning-Enabled FinTech Applications.
- AttSum: A Deep Attention-Based Summarization Model for Bug Report Title Generation.