Dr Ziyun Ding PhD, FHEA

Department of Mechanical Engineering
Associate Professor

Contact details

Email: z.ding@bham.ac.uk
Twitter: @ziyunding

Address: University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr Ziyun Ding is an Associate Professor in the Department of Mechanical Engineering, and the deputy head of the Biomedical Engineering Research Group in the School of Engineering.

Her research is driven by the pressing societal need to improve mobility, independence, and quality of life for individuals affected by musculoskeletal and neurological impairments — challenges that are intensifying globally with ageing populations and rising healthcare demands. Dr Ding’s research focuses on advancing understanding of how muscle-tendon and neuro-musculoskeletal dynamics adapt to trauma, degenerative diseases, and ageing. By combining experimental biomechanics, wearable technologies, computational neuromusculoskeletal modelling and AI, her vision is to unravel the complex mechanisms underlying human movement. New knowledge and insights are translated into intelligent, evidence-based solutions for assistive technologies, surgeries and rehabilitation, ultimately enhancing global well-being and shaping a more sustainable future.

Qualifications

Fellow of The Higher Education Academy, 2021
Associate Fellow of The Higher Education Academy, 2019
PhD in Engineering, University of Liverpool, UK, 2013
MEng in Mechanical Engineering, Nanjing University of Aeronautics and Astronautics, China, 2009
BEng in Mechanical Engineering, Nanjing University of Aeronautics and Astronautics, China, 2006

Biography

Ziyun received her PhD in 2013 from the University of Liverpool. Her PhD thesis entitled “Manual Assembly Modelling and Simulation for Ergonomics Analysis” was conducted across the Virtual Engineering Centre (VEC) and the School of Engineering.

She joined in the Department of Bioengineering, Imperial College London, as a research associate in 2014. Her research focused on the development and validation of personalised musculoskeletal model. The high-fidelity computational model has contributed to improve the movement strategies and rehabilitation technologies for patients with knee osteoarthritis and anterior cruciate ligament (ACL) injury. She joined in the Royal British Legion Centre for Blast Injuries Studies (CBIS), Imperial College London in 2015. Based on computational musculoskeletal modelling her research aimed to design and optimise the mitigation strategies for lower limb military amputees in order to reduce the injury burden in the amputated musculoskeletal system. She joined in the Department of Mechanical Engineering, University of Birmingham in 2019 as a lecturer.

Teaching

LI Mechanics 2
Advanced Mechanics
Bio-medical and Micro Engineering

Postgraduate supervision

Students with interests in computational biomechanics, human movement sciences, rehabilitation engineering, assistive technologies (including prosthetics and orthotics), wearable technologies, biomedical signal processing and control, and the application of AI in healthcare and biomechanics are encouraged to get in touch.

Research

Ziyun’s research applies model-based methodologies to study patient-specific mappings between locomotion, musculoskeletal system and mechanics, in order to design and develop clinically viable technologies for patient-accessible and patient-centred interventions, and targets at potential audients with lower limb musculoskeletal injury and disease.

Publications

Journal Article

1. Ding Z, Güdel M, Smith SHL, Ademefun RA, Bull AMJ., (2019), A Femoral Clamp to Reduce Soft Tissue Artefact: Accuracy and Reliability in Measuring Three-Dimensional Knee Kinematics During Gait, Journal of Biomechanical Engineering.

2. Ding Z, Tsang C, Nolte D, Kedgley AE, Bull AMJ., (2019), Improving musculoskeletal model scaling using an anatomical atlas: the importance of gender and anthropometric similarity to quantify joint reaction forces, IEEE Transactions on Biomedical Engineering.

3. Klemt C, Nolte D, Ding Z, Rane L, Quest RA, Finnegan ME, Walker M, Reilly P, Bull AMJ., (2019), Anthropometric Scaling of Anatomical Datasets for Subject-Specific Musculoskeletal Modelling of the Shoulder, Annals of Biomedical Engineering, 47(4): 924-936.

4. Rane L, Ding Z, McGregor AH, Bull AMJ., (2019), Deep learning for musculoskeletal force prediction, Annals of Biomedical Engineering, 47(3): 778-789

5. Xu R, Ming D, Ding Z, Bull AMJ., (2019), Extra Excitation of Biceps Femoris during NMES Reduces Knee Medial Loading, Royal Society Open Science, 6(3): 181545

6. Ding Z, Azmi NL, Bull AMJ., (2019), Validation and use of a musculoskeletal gait model to study the role of functional electrical stimulation, IEEE Transactions on Biomedical Engineering, 66: 892-897

7. Azmi NL, Ding Z, Xu R, Bull AMJ., (2018), Activation of biceps femoris long head reduces tibiofemoral anterior shear force and tibial internal rotation torque in healthy subjects, PLoS ONE,13(1): e0190672

8. Nolte D, Tsang CK, Zhang KY, Ding Z, Kedgley AE, Bull, AMJ., (2016),Non-linear scaling of a musculoskeletal model of the lower limb using statistical shape models, Journal of biomechanics, 49(14), 3576-3581

9.Ding Z, Nolte D, Tsang CK, Cleather DJ, Kedgley AE, Bull AMJ., (2015), In Vivo Knee Contact Force Prediction Using Patient-Specific Musculoskeletal Geometry in a Segment-Based Computational Model., Journal of Biomechanical Engineering,138(2)

10. Ding Z, Hon B., (2013), Constraints analysis and evaluation of manual assembly, CIRP Annals, 62(1):1-4

View all publications in research portal