Research Interests
Including but not limited to:
- 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. - 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. - Uncertainty Estimation and Calibration in Imperfect Models
Improving model interpretability and decision-making by quantifying uncertainty and ensuring well-calibrated predictions. - 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.
Discover More
- Faculty of Engineering and Physical Science
- School of Electronics, Electrical Engineering and Computer Science
- Centre for Intelligent Sustainable Computation
- Personal website