Torch

Dr Qingde Li

Lecturer

Faculty and Department

  • Faculty of Science and Engineering
  • School of Engineering and 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.

His current research interests are in the areas of computer graphics and mixed reality technology, with a particular focus on high precision geometric modelling of real objects.

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.

Conference Proceeding

Thin Implicit Utah Teapot: Design for Additive Manufacturing

Qi, Q., & Li, Q. (2018). Thin Implicit Utah Teapot: Design for Additive Manufacturing. In Proceedings iThings/GreenCom/CPSCom/SmartData/Blockchain/CIT/Cybermatics 2018doi:10.1109/Cybermatics_2018.2018.00320

Journal Article

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), https://doi.org/10.1186/s42492-018-0009-y

A Survey of the Methods on Fingerprint Orientation Field Estimation

Bian, W., Xu, D., Li, Q., Cheng, Y., Jie, B., & Ding, X. (2019). A Survey of the Methods on Fingerprint Orientation Field Estimation. IEEE access : practical innovations, open solutions, 7, 32644-32663. https://doi.org/10.1109/access.2019.2903601

High precision implicit modeling for patient-specific coronary arteries

Hong, Q., Li, Q., Wang, B., Liu, K., & Qi, Q. (2019). High precision implicit modeling for patient-specific coronary arteries. IEEE access : practical innovations, open solutions, 7, 72020-72029. https://doi.org/10.1109/access.2019.2920113

Prior knowledge-based deep learning method for indoor object recognition and application

Ding, X., Luo, Y., Li, Q., Cheng, Y., Cai, G., Munnoch, R., …Wang, B. (2018). Prior knowledge-based deep learning method for indoor object recognition and application. Systems Science and Control Engineering, 6(1), 249-257. https://doi.org/10.1080/21642583.2018.1482477

Prior knowledge-based deep learning method for indoor object recognition and application

Ding, X., Luo, Y., Li, Q., Cheng, Y., Cai, G., Munnoch, R., …Wang, B. (2018). Prior knowledge-based deep learning method for indoor object recognition and application. Systems Science and Control Engineering, 6(1), 249-257. https://doi.org/10.1080/21642583.2018.1482477

Postgraduate supervision

Dr Li welcomes applications in the areas of computer graphics, geometric modelling and scientific simulation. Deep learning in geometric modelling and processing.