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Dr Xinhui Ma

Faculty and Department

  • Faculty of Science and Engineering
  • School of Computer Science

Qualifications

  • PhD (University of Birmingham)

Summary

Dr Ma's research areas lie in Visual Computing and Data Science. Particularly interested in Image Analysis, Digital Twin, Virtual Reality, Augmented Reality, Computer Graphics; Data Mining, Machine Learning.

His expertise has applications in Digital Healthcare, Green Energy and Advanced Manufacturing. Dr Ma is a holder of Wellcome Trust Seed Award.

Teaching Modules:

Reality Time Graphics

3D Computer Graphics

Virtual Environment

Mixed Reality Development

Advanced Rendering and Virtual Environment

Recent outputs

View more outputs

Conference Proceeding

A Multi-Modal Deep Learning Approach to the Early Prediction of Mild Cognitive Impairment Conversion to Alzheimer's Disease

Rana, S. S., Ma, X., Pang, W., & Wolverson, E. (2020). A Multi-Modal Deep Learning Approach to the Early Prediction of Mild Cognitive Impairment Conversion to Alzheimer's Disease. In 2020 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT) (9-18). https://doi.org/10.1109/BDCAT50828.2020.00013

Journal Article

GANS-based data augmentation for citrus disease severity detection using deep learning

Zeng, Q., Ma, X., Cheng, B., Zhou, E., & Pang, W. (2020). GANS-based data augmentation for citrus disease severity detection using deep learning. IEEE Access, 8, 172882-172891. https://doi.org/10.1109/ACCESS.2020.3025196

A 3D cephalometric protocol for the accurate quantification of the craniofacial symmetry and facial growth

Pinheiro, M., Ma, X., Fagan, M. J., McIntyre, G. T., Lin, P., Sivamurthy, G., & Mossey, P. A. (2019). A 3D cephalometric protocol for the accurate quantification of the craniofacial symmetry and facial growth. Journal of Biological Engineering, 13(1), https://doi.org/10.1186/s13036-019-0171-6

Towards additive manufacturing oriented geometric modeling using implicit functions

Li, Q., Hong, Q., Qi, Q., Ma, X., Han, X., & Tian, J. (2018). Towards additive manufacturing oriented geometric modeling using implicit functions. Visual Computing for Industry, Biomedicine, and Art, 1(1), Article 9. https://doi.org/10.1186/s42492-018-0009-y

Surface fitting for quasi scattered data from coordinate measuring systems

Mao, Q., Liu, S., Wang, S., & Ma, X. (2018). Surface fitting for quasi scattered data from coordinate measuring systems. Sensors, 18(1), 214. https://doi.org/10.3390/s18010214

Research interests

Digital Healthcare, Medical Image Analysis

Data Science, Machine Learning

Digtial Twin, Computer Graphics

Virtual Reality, Augmented Reality

CAD/CAM, Finite Element Analysis

Project

Funder

Grant

Started

Status

Project

3D Analysis of Maxillofacial Growth

Funder

Wellcome Trust

Grant

£98,344.00

Started

1 July 2017

Status

Complete

Postgraduate supervision

Dr Ma welcomes applications in Digital Twin, Virtual Reality, Augmented Reality, Computer Vision, Medical Image Analysis, Data Science and Machine Learning etc.

Current PhDs:

Eamonn Tuton, Primary supervisor, “Digital Twin Logistics of Operations and Maintenance for Offshore Wind Farms”.

Haider Alkaraawi, Primary supervisor, “Machine Learning and Data Mining for Cancer Care”.

Completed PDRAs and visiting researchers:

PostDoc: Dr Manuel Pinheiro, Wellcome Trust project “3D analysis of maxillofacial growth in patients with cleft lip and palate”, 09/2017 – 02/2019.

Visiting Researcher: Dr Qingmao Zeng, China Scholarship Council project “Deep learning for plant disease detection”, 08/2018 – 08/2019.

Awards and prizes

Wellcome Trust Seed Award in Science

2017

Membership/Fellowship of professional body

Fellow of the Higher Education Academy

2013

Research assessment service

EPSRC peer reviewer

2018

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