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 disorders and to develop effective treatments. Currently open to PhD applications.
Current positions
Lecturer in Data Science
School of Engineering Mathematics and Technology
Contact
Press and media
Many of our academics speak to the media as experts in their field of research. If you are a journalist, please contact the University’s Media and PR Team:
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 disorders and to develop effective treatments.
Research interests
I have a broad range of research interests across the field of AI. My recent research interests lie in the applications of AI and bioinformatics in medical and biological science, especially mental health and neuroscience, including: AI algorithms especially deep neural networks, personalised treatment and diagnosis, early detection, treatment response prediction, disease monitoring, risk evaluation, drug discovery, cell profiling, prediction and inference modelling, brain imaging, genomic analysis, EHR analysis, smart/wearable sensors, MCDA in healthcare, biomedical signal processing, natural language processing, visual SLAM and scene understanding.
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
20/12/2024Changes in iPSC-Astrocyte morphology reflect Alzheimer’s disease patient clinical markers
Stem Cells
FAGD-Net: Feature-augmented grasp detection network based on efficient multi-scale attention and fusion mechanisms
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
Real-world effects of antidepressants for depressive disorder in primary care: population-based cohort study
British Journal of Psychiatry