Dr Qingde Li

Dr Qingde Li

Lecturer

Faculty and Department

  • Faculty of Science and Engineering
  • School of Computer Science

Summary

Dr Qingde Li has been a lecturer in computer science at the University of Hull since 2001. Previously he was Professor and Deputy Head of Mathematics and Computer Science at Anhui Normal University, China.

Dr Li's research findings have been published in the world's most prestigious graphics journals including ACM Transactions on Graphics, IEEE Transactions on Visualization and Computer Graphics, and IEEE Transactions on Medical Imaging.

Dr Li@Google scholar: https://scholar.google.co.uk/citations?user=abSAMUkAAAAJ&hl=en

Dr Li's teaching covers a wide range of subjects, ranging from calculus, probability & statistics in mathematics (taught in China) to 3D graphics in computer science.

Recent outputs

View more outputs

Journal Article

ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation

Li, Z., Zheng, Y., Shan, D., Yang, S., Li, Q., Wang, B., …Shen, D. (in press). ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation. IEEE Transactions on Medical Imaging, https://doi.org/10.1109/tmi.2024.3363190

Using outlier elimination to assess learning-based correspondence matching methods

Ding, X., Luo, Y., Jie, B., Li, Q., & Cheng, Y. (2024). Using outlier elimination to assess learning-based correspondence matching methods. Information Sciences, 659, Article 120056. https://doi.org/10.1016/j.ins.2023.120056

LViT: Language meets Vision Transformer in Medical Image Segmentation

Li, Z., Li, Y., Li, Q., Wang, P., Guo, D., Lu, L., …Hong, Q. (2024). LViT: Language meets Vision Transformer in Medical Image Segmentation. IEEE Transactions on Medical Imaging, 43(1), 96-107. https://doi.org/10.1109/TMI.2023.3291719

Consensus Adversarial Defense Method Based on Augmented Examples

Ding, X., Cheng, Y., Luo, Y., Li, Q., & Gope, P. (2022). Consensus Adversarial Defense Method Based on Augmented Examples. IEEE Transactions on Industrial Informatics, https://doi.org/10.1109/TII.2022.3169973

High-quality vascular modeling and modification with implicit extrusion surfaces for blood flow computations

Hong, Q., Li, Q., Wang, B., Tian, J., Xu, F., Liu, K., & Cheng, X. (2020). High-quality vascular modeling and modification with implicit extrusion surfaces for blood flow computations. Computer Methods and Programs in Biomedicine, 196, Article 105598. https://doi.org/10.1016/j.cmpb.2020.105598

Research interests

Dr Li's current research interests are in the areas of computer graphics, visual and tangible computing, as well as their applications in mixed reality environment , including

(1). High precision geometric reconstruction of vascular and neural structures.

(2). Deep learning on shape understanding and geometric information processing.

(3). Tactile modelling and haptic effects programming.

(4). Environmental geometry-aware wearable devices.

Postgraduate supervision

Dr Li welcomes applications in the areas of visual and tangible computing, deep learning in geometric information processing and scientific simulation, cloud-based collaborative geometric design in mixed reality environment, as well as developing environmental geometry-aware wearable devices.

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