Adaptive AI & Human Dynamics Lab 
A2HD studies human-centered AI for human dynamics. We build adaptive intelligent systems that combine rigorous machine learning with real-world understanding of human behaviour, context, and decision-making.
Our work spans generative AI, dialogue systems, mobile and ubiquitous computing, context-aware intelligence, and intelligent services, with applications in personalized systems, education, healthcare, transportation, and smart cities.
Research Themes
1. Adaptive and Personality-Aware LLMs
We study how large language models can be adapted to user traits, task requirements, and domain constraints. This includes personality-aware dialogue systems, adaptive persona prompting, task-dependent model behaviour, and efficient control of reasoning style.
2. Trustworthy Generative AI
We investigate bias, robustness, privacy, and safety in generative AI systems, especially when models are deployed in education and human-facing decision support.
3. Human Dynamics and Context-Aware Intelligence
We develop models and systems for understanding human behaviour from heterogeneous signals, with emphasis on context awareness, privacy preservation, and actionable insights.
4. Intelligent Services for Real-World Domains
We design AI systems for practical domains such as personalized learning, mobility, healthcare, and automotive diagnostic services.
Representative Ongoing Directions
- Adaptive personality profiling for real-time dialogue systems
- Personality-aware conversational AI and dialogue transformation
- Task-dependent bias detection and mitigation in educational generative AI
- Multi-agent language teaching and contextual simulation
- Knowledge graph-driven LLMs for automotive diagnostic services
- Privacy-preserving mobile crowdsensing and human activity sensing
- Data-driven intelligence for transportation and movement analysis
Why Join A2HD
- Clear research identity: a focused agenda around adaptive AI, human dynamics, and real-world deployment
- Publication-oriented culture: research aimed at strong journals and conferences in AI, data science, ubiquitous computing, and information systems
- Funded research directions: active projects across generative AI, privacy-preserving analytics, knowledge graphs, transportation, and intelligent services
- Real-world resources: access to computing infrastructure and application-driven datasets
- Close mentorship: a growing lab where students and fellows can help shape new directions from an early stage
Selected Strengths
- Research published in venues such as ACM TOIS, IEEE TMC, IEEE TKDE, WWW, and IEEE INFOCOM
- Best Paper Awards at IEEE INFOCOM and ICNP
- Interdisciplinary environment within Lingnan University’s School of Data Science
Open Positions
We are recruiting:
- Research Postgraduate (RPG/PhD) students: View RPG opportunities
- Postdoctoral fellows: View postdoc opportunities
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Contact
Prospective candidates are welcome to email jiaxingshen@LN.edu.hk with a CV and a short note on research fit.