qingde-li

Dr Qingde Li

Lecturer

Faculty and Department

  • Faculty of Science and Engineering
  • Department of Computer Science and Technology

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

Undergraduate

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.

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

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.