Staff Profile

I am a lecturer in Computer Graphics and Computer Vision with a focus on image processing using Deep Learning.

Brief CV

2021 - Present: Lecturer in Visual Computing, the School of Computing, Newcastle University, UK. 

Education

PhD in recognition of a thesis entitled "Accurate Real-Time Complex Cutting in Finite Element Modeling", Newcastle University, UK. 

University Administrative Role

Degree Programme Director for MSc Data Analytics Degree Apprenticeship

Athena SWAN SAT Chair of the School of Computing

External Activities

BBSRC Peer Reviewer

External Examiner for the MSc Artificial Intelligence programme of the University of Essex. 

Research Summary

My research background is originally in Computer Graphics, with specific interests in optimising the FEM (Finite Element Method) based systems of linear equations using matrices to achieve challenging accurate cutting of surfaces in real-time.

My current research interest is in the way in which Machine Learning, especially Deep Learning techniques, can be used to expand the application range of Computer Graphics and boost the solving speed of large-scale datasets. Specifically, practical applications of interest lie in Medical Imaging Processing, Remote Sensing Image Processing and Geometric Deep Learning.

• CSC8628 Image Informatics
• CSC8409 Capstone Project for Data Analytics Degree Apprenticeship

• Articles

  • Zhu Y, Wang S, Xin T, Zhang Z, Zhang H. Partition-A-Medical-Image: Extracting Multiple Representative Sub-regions for Few-shot Medical Image Segmentation. IEEE Transactions on Instrumentation and Measurement 2024, 73, 5016312.
  • Cheng Z, Wang S, Xin T, Zhou T, Zhang H, Shao L. Few-Shot Medical Image Segmentation via Generating Multiple Representative Descriptors. IEEE Transactions on Medical Imaging 2024, epub ahead of print.
  • Cheng Z, Zhu Y, Wang S, Xin T, Zhang H. Cascaded Alternating Refinement Transformer for Few-shot Medical Image Segmentation. ACM Transactions on Intelligent Systems and Technology 2024.
  • Suresh MD, Xin T, Cook SM, Evans D. Bugs and Bytes: Entomological Biomonitoring Through the Integration of Deep Learning and Molecular Analysis for Merged Community and Network Analysis. Agricultural and Forest Entomology 2024, 27(1), 35-49.
  • Suresh MD, Xin T, Cook SM, Evans DM. Bugs and bytes: Entomological biomonitoring through the integration of deep learning and molecular analysis for merged community and network analysis. Agricultural and Forest Entomology 2024, epub ahead of print.
  • Akbulut O, McLaughlin L, Xin T, Forshaw M, Holliman NS. Visualizing ordered bivariate data on node-link diagrams. Visual Informatics 2023, 7(3), 22-36.
  • Wang Z, Xin T, Wang S, Zhang H. Depth-embedded instance segmentation network for urban scene parsing. Journal of Intelligent and Fuzzy Systems 2022, 42(3), 1269-1279.

• Book Chapter

  • Cuff JP, Deivarajan Suresh M, Dopson MEG, Hawthorne BSJ, Howells T, Kitson JJN, Miller KA, Xin T, Evans DM. A roadmap for biomonitoring in the 21st century: merging methods into metrics via ecological networks. In: David A. Bohan, Alex J. Dumbrell, ed. Advances in Ecological Research. Elsevier, 2023.

• Conference Proceedings (inc. Abstracts)

  • Cheng Z, Wang S, Xin T, Zhang H. Frequency-aware Adaptive Filtering Network for Few-Shot Medical Image Segmentation. In: 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 2024, IEEE Computer Society.
  • Zhu Y, Wang S, Xin T, Zhang H. Few-shot Medical image segmentation via a region-enhanced prototypical transformer. In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2023. 2024, Marrakesh, Morocco: Springer.
  • Wang Z, Zhang X, Wang S, Xin T, Zhang H, Lu J. Multi-scale Spatial Transformer Network For Lidar-camera 3D Object Detection. In: 2021 International Joint Conference on Neural Networks (IJCNN). 2021, IEEE. In Preparation.
  • Xin T, Marris P, Mihut A, Ushaw G, Morgan G. Accurate real-time complex cutting in finite element modeling. In: Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018). 2018, Madeira, Portugal: SciTePress.