Shaping Neurological Disease Data with AI: Imaging and Language Models
The CS seminar on the 25th Feb will be delivered by Prof Qiang Liu, University of Bristol on Shaping Neurological Disease Data with AI. The seminar will start at 14:30 in Harrison 203.
| A Computer Science seminar | |
|---|---|
| Date | 25 February 2026 |
| Time | 14:30 to 16:30 |
| Place | Harrison Building 203 |
Event details
Abstract
Neurological diseases such as Alzheimer's disease and epilepsy generate complex, heterogeneous data spanning cellular imaging, brain scans, and unstructured clinical text. This talk presents AI-driven approaches that integrate imaging and language models to transform such data into structured, interpretable insights. Deep learning methods applied to high-content cellular and brain imaging reveal disease-relevant morphological and structural patterns, enabling scalable phenotyping, biomarker discovery, and drug screening. In parallel, large language model–enhanced natural language processing pipelines extract and standardise clinically meaningful information from free-text medical records and biomedical literature. Together, these approaches demonstrate how AI can reshape neurological disease data to support translational research, precision medicine, and improved understanding of disease mechanisms.
Speaker:
Qiang Liu is a senior lecturer in the Department of Engineering Mathematics and Technology at the University of Bristol. Additionally, he holds the position of honorary research scientist in the Department of Psychiatry at the University of Oxford, where he conducted his postdoctoral research. He obtained his PhD in Computer Science from the University of Essex, UK in 2019. He has been working on mental health and healthcare robotics. His aim is to develop and apply state-of-the-art AI and bioinformatic techniques to gain a deeper understanding of neurological disorders and to develop effective treatments. His research interests lie in the applications of AI and bioinformatics in medical, biological science and healthcare robotics, especially neurological and mental health disorders, including: personalised treatment, early diagnose, risk assessment, disease progression monitoring, treatment response prediction, prognostic and diagnostic modelling, drug discovery, information retrieval, etc.
Location:
Harrison Building 203