Research Interests

Including but not limited to:

1. Robust Machine Learning under Imperfect and Complex Conditions
   Developing resilient algorithms that perform reliably in the presence of noisy data, weak supervision, or dynamic environments.
2. Safety and Reliability of Large Language Models (LLMs)
   Investigating methods to assess and enhance the trustworthiness of LLMs, especially when deployed in real-world, high-stakes scenarios.
3. Uncertainty Estimation and Calibration in Imperfect Models
   Improving model interpretability and decision-making by quantifying uncertainty and ensuring well-calibrated predictions.
4. Applications in Healthcare and Medical Imaging with Imperfect Data
   Applying robust machine learning techniques to clinical and imaging data, which often contain missing values, noise, or limited annotations.

Make a PhD enquiry

Current Research Opportunities

• Enhancing Safety, Reliability, and Robustness in Large Language and Multimodal Large Language Models
• Advancing Robust Artificial Intelligence for Transformative Healthcare Applications

Discover More

• Faculty of Engineering and Physical Science
• School of Electronics, Electrical Engineering and Computer Science
• Centre for Intelligent Sustainable Computation
• Personal website