Dr. Peng LI


Dept of Engineering Mathematics
University of Bristol

Intelligent Systems Lab

Merchant Venturers' Building
Woodland Road
Clifton, Bristol
United Kingdom




Current Group at UoB:

Intelligent Systems Laboratory

Previous Group at UCL:

Prince Vision Lab


Last Update


 Peng Li

I am a postdoctoral research associate at the Department of Engineering Mathematics with Dr. Colin Campbell. Before coming to Bristol, I was in the Department of Computer Science at University College London, with Dr. Simon J. D. Prince.

My research interests include computer vision, machine learning, image analysis and medical signal analysis. In particular, Bayesian approach to face recognition and facial keypoint localization, decision fusion, kernel-based methods, object detection and recognition and imbalanced data problem etc.

My current research is machine learning methods for bioinformatics. At PVL, my research focused on face recognition based on probabilistic approaches. E.g. I proposed to use the same probabilistic model for both face registration and recognition, and proposed a Context based additive logistic model to improve facial keypoint localization under large pose variation. Our probabilistic model is one of the best models in the Labelled Faces in the Wild (LFW) database.


Ph.D. (2006) Nanyang Technological University, Singapore, supervised by  A/P Kap Luk CHAN  & S. M. Krishnan

B. Eng. (1993), M. Eng. (1998) North China Electric Power University, China.

Working Experience

Mar. 2007 - Dec. 2007, Jun. 2010 – Now, University of Bristol, Postdoctoral Research Associate.

Jan. 2008 - Present, University College London, Postdoctoral Research Associate.

Sep. 2005 - Jan. 2007, Stratech Systems Ltd. Singapore, Software Engineer (Computer Vision).

Jul. 2003 - Nov. 2003, July, 2004---Nov. 2004, Nanyang Technological University, Singapore, Teaching Assistant. 

Jul. 1998 - Apr. 2002, North China Electric Power University, China, Lecturer.

Recent Publications

Peng Li, Yun Fu, Umar Mohammed, James Elder, and Simon J.D. Prince. Probabilistic Models for Inference About Identity. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 34, No. 1, pages 144-157, 2012. [pdf] [BibTex]

Yiming Ying and Peng Li, Distance metric learning with eigenvalue optimization. Journal of Machine Learning Research (Special topics on kernel and metric learning), 2011 (to appear). [pdf] [BibTex]

Peng Li, Jonathan Warrell, Jania Aghajanian and Simon J. D. Prince, Context based additive logistic model for facial keypoint localization, 21th British Machine Vision Conference (BMVC), 2010. [pdf] [BibTex]

Peng Li and Simon J. D. Prince. Advance in Face Image Analysis: Techniques and Technologies, chapter Probabilistic Methods for Face Registration and Recognition (In Press). Idea Group Publishing, 2010. [BibTex] PLDA Matlab Code

Yoshiki Mizukami, Katsumi Yamaguchi, Jonathan Warrell, Peng Li, Simon J. D. Prince, CUDA Implementation of Deformable Pattern Recognition and its Application to MNIST Handwritten Digit Database, In 20th International Conference on Pattern Recognition (ICPR), 2010. [BibTex]

Peng Li and Simon. J. D. Prince. Joint and Implicit Registration for Face Recognition, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1510–1517, 2009. (Oral presentation: acceptance rate 4.1%)  [pdf]  [ppt]  [BibTex]

J. Aghajanian, J. Warrell, S.J.D. Prince, P. Li and J.L. Rohn and B.Baum. Patch-based Within-Object Classification. In IEEE International Conference on Computer Vision (ICCV), 2009.  [pdf]  [BibTex]

Peng Li, Yiming Ying and Colin Campbell. A Variational Approach to Semi-Supervised Clustering. In European Symposium on Artificial Neural Networks (ESANN), pages 11–16, 2009. [pdf]  [BibTex]

Yiming Ying, Peng Li, Collin Compbell. A marginalized variational Bayesian approach to the analysis of array data. In BMC proceedings, volume 2 Suppl 4, 2008. [pdf]  [BibTex]

Peng Li, Kap Luk Chan and Wen Fang. Hybrid Kernel Machine Ensemble for Imbalanced Data Sets. In 18th International Conference on Pattern Recognition (ICPR’06), volume 1, pages 1108–1111, 2006.  [pdf]  [BibTex]

Peng Li, Kap Luk Chan, Sheng Fu and Shankar M. Krishnan. Neural Networks in Healthcare: Potential and Challenges, chapter A Concept Learning-based Patient-adaptable Abnormal ECG Beat Detector for Long-term Monitoring of Heart Patients, pages 105–128. Idea Group Publishing, 2006.   [pdf]  [BibTex]

Peng Li, Hai Rong Sun, Kap Luk Chan, Li Hui Zhou, Shankar M. Krishnan. Stacking of SVMs for abnormal region screening in endoscopic images using multisize patches. In Proceedings of 2005 International Conference on Machine Learning and Cybernetics, volume 5, pages 3242–3247, 2005.   [BibTex]

Peng Li, Kap Luk Chan and Shankar M. Krishnan. Learning a Multi-Size Patch-Based Hybrid Kernel Machine Ensemble for Abnormal Region Detection in Colonoscopic Images. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), volume 2, pages 670–675, 2005. . (Acceptance rate 27.9%)     [pdf]  [BibTex]

Peng Li, Kap Luk Chan, Sheng Fu and Shankar M. Krishnan. An Abnormal ECG Beat Detection Approach for Long-Term Monitoring of Heart Patients Based on Hybrid Kernel Machine Ensemble. In N. C. Oza, R. Polikar, J. Kittler, and F. Roli, editors, Multiple Classifier Systems, volume 3541 of Lecture Notes in Computer Science, pages 346–355. Springer, 2005. [pdf] [BibTex]

Peng Li, Kap Luk Chan, Y. W. Chan. A mixed SVM-based hierarchical learning approach for abnormal ECG beat recognition. In Proceedings of the 1st International Conference on Bioengineering (IBEC 2004), Singapore, 2004.  [pdf]  [BibTex]

Peng Li, Kap Luk Chan, Shankar M. Krishnan and Yan Gao. Detecting Abnormal Regions in Colonoscopic Images by Patch-based Classifier Ensemble. In 17th International Conference on Pattern Recognition (ICPR’04), volume 3, pages 774–777, 2004. (Acceptance rate 35.1%)   [pdf]  [BibTex]

Peng Li, Shankar M. Krishnan, Kap Luk Chan and Yan Gao. Abnormal Region Detection in Colonoscopic Images using Novelty Detection Technique. In Proceedings of 7th International Workshop on Advanced Image Technology (IWAIT 2004), Singapore, 2004.   [BibTex]

Ph.D. Thesis:

Peng Li. Kernel Machines and Classifier Ensemble Learning for Biomedical Applications. PhD thesis, Nanyang Technological University, Singapore, 2006.   [pdf]  [BibTex]


Current Supervisor:   Dr. Colin Campbell

Previous Supervisor:  Dr. Simon J. D. Prince

Ph.D. Thesis Advisor: Dr.  Kap Luk Chan

Previous Teammate:  Dr. Lei Wang

Previous Teammate:  Dr. Yiming Ying