Dr Qiang Liu
PhD
Expertise
My research interests are to develop and apply state-of-the-art AI and bioinformatic techniques to gain a deeper understanding of neurological and mental health disorders, and to develop effective treatments.
Current positions
Lecturer in Data Science
School of Engineering Mathematics and Technology
Contact
Press and media
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Biography
He has been working on mental health and healthcare robotics. He has cross-disciplinary interests in mental health illnesses, neuroscience and AI. His aim is to develop and apply state-of-the-art AI and bioinformatic techniques to gain a deeper understanding of neurological and mental health disorders and to develop effective treatments.
Research interests
I have a broad range of research interests across the field of AI. My research interests lie in the applications of AI and bioinformatics in medical, biological science and healthcare robotics, especially neurological and mental health disorders, including:
- Applications: personalised treatment, early diagnose, risk assessment, disease progression monitoring, treatment response prediction, prognostic and diagnostic modelling, drug discovery, information retrieval, etc.
- Algorithms: generative AI, machine learning, statistical modelling, MCDA, etc.
- Data types: EHR, neuroimaging and cellular imaging, omics data, biomedical signals, data from smart/wearable sensors, longitudinal and cross-sectional data, etc.
I am currently open to PhD applications.
Projects and supervisions
Research projects
Cryptic Chatter: Decoding Multicellular Interactions with AI Microscopy
Principal Investigator
Role
Co-Investigator
Managing organisational unit
School of Engineering Mathematics and TechnologyDates
01/12/2024 to 31/07/2025
Feasibility of Artificial Intelligence (AI) for Patient Registries
Principal Investigator
Role
Co-Investigator
Managing organisational unit
School of Engineering Mathematics and TechnologyDates
01/12/2024 to 31/07/2025
Using artificial intelligence to decode morphological signatures for Alzheimer's disease
Principal Investigator
Managing organisational unit
School of Engineering Mathematics and TechnologyDates
01/04/2024 to 31/07/2024
Using artificial intelligence to identify disease phenotypes in Alzheimer’s disease through cellular morphology
Principal Investigator
Managing organisational unit
School of Engineering Mathematics and TechnologyDates
01/02/2024 to 31/07/2024
Using artificial intelligence to decode morphological signatures underpinning neural development
Principal Investigator
Role
Principal Investigator
Managing organisational unit
School of Engineering Mathematics and TechnologyDates
01/12/2023 to 30/06/2024
Publications
Selected publications
14/06/2023Predicting outcomes at the individual patient level: what is the best method?
BMJ Mental Health
Development and validation of a meta-learner for combining statistical and machine learning prediction models in individuals with depression
BMC Psychiatry
Personalised treatment for cognitive impairment in dementia: development and validation of an artificial intelligence model
BMC Medicine
Recent publications
24/01/2025An AG-RetinaNet for Embryonic Blastomeres Detection and Counting
International Journal of Imaging Systems and Technology
Changes in iPSC-Astrocyte morphology reflect Alzheimer’s disease patient clinical markers
Stem Cells
FAGD-Net
Applied Sciences
Model-free visual servoing based on active disturbance rejection control and adaptive estimator for robotic manipulation without calibration
Industrial Robot: An International Journal
Real-time Support Terrain Mapping and Terrain Adaptive Local Planning for Quadruped Robots
IEEE Robotics and Automation Letters
Teaching
Sammy Shorthouse
Hans Johnson
Ziwen Yu