
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
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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 recent research interests lie in the applications of AI and bioinformatics in medical and biological science, especially neurological and mental health disorders, including: AI algorithms especially deep neural networks, digital health, personalised treatment and diagnosis, early detection, risk evaluation, disease monitoring, treatment response prediction, drug discovery, cell profiling, brain imaging, genomic analysis, EHR analysis, smart/wearable sensors, biomedical signal processing, prognostic and diagnostic predictions, prediction and inference modelling, MCDA in healthcare, 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
01/01/2025An 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: 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