I am passionate in exploring new knowledge through teaching and working with my students. I have been teaching computer vision, machine learning and AI for many years, enjoying and experiencing the rapid evolution in these fields. As a researcher, I am interested in applying machine learning to image and natural language understanding, with a particular focus on the medical domain. I have been working with a number of NHS hospitals, as well as hospitals in Europe and Asia, on a wide range of projects including: the development of automated tracking of fine movements of surgical instruments in eye and other microsurgeries; digital retinal image analysis to understand various eye and systemic conditions; time-lapse bacterial cell image analysis for understanding mycobacterial persistence. Beyond my passion in healing and care through medicine, I am also fascinated by the wonders of nature and keen to be part of it. This may be slightly reflected through the work that I participated in with the Royal Botanic Gardens, Kew, on Herbarium Image Data Analysis as well as the National Plant Phenomics Centre on heritage plants.
Computer vision, Image processing, Machine learning, Natural language processing
Moorfields Eye Hospital; Royal Surrey County Hospital; Frimley Heath NHS; UCL University NHS hospitals; Bedford Hospital; the Surrey and Sussex NHS Trust; St George’s Hospital; Royal Botanic Gardens, Kew; School of Medicine, Dentistry and Biomedical Science, Queen’s University, Belfast; Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine; Primary Care Health Sciences, University of Oxford; Zhongshan Ophthalmic Centre, Sun Yat-Sen University, China; NHMRC Clinical Trials Centre, The University of Sydney, Australia; The University of Melbourne, Australia; Department of Medicine and Science of Ageing, Ophthalmology Clinic, University "G. d'Annunzio" Chieti-Pescara, Italy.
Key Research Projects
- Innovate UK - Newton Fund: Automated Telemedicine Enabled Screening for Eye Diseases Using an Affordable and Simple to Use Smartphone Based Imaging Device.
- Industry Innovation Fund: Deep Learning for Medicine.
- Innovate UK - Emerging and Enabling Fund: Automated Luggage Identification.
- Innovate UK Knowledge Transfer Partnership: Data Science for Sustainable Homes.
- EPSRC funded Collaborative Hub for Advancing Interdisciplinary Research: Modelling Mycobacterial Persistence.
- The ICURe Innovation: Automatic Digital Retinal Image Analysis for Diabetic Retinopathy Screening and Eye Disease Monitoring.
- King Abdulaziz City for Science and Technology & Ministry of Economy and Planning: Statistical Modelling for Diabetic Retinopathy Detection.
- BBSRC (Biotechnology and Biological Sciences Research Council): Investigation of stochastic variations in growth rate as the mechanism of drug tolerance in Mycobacterium tuberculosis.
- EPSRC (Engineering and Physical Sciences Research Council): Automatic Reading of Digital Fundus Images for Large scale Eye Epidemiology Studies.
- EPSRC funding: Minimal access surgical training, enhancement and reporting software (MASTERS).
- Moorfields Eye Hospital: Digital Fundus Image Analysis for Screening, Population-based Study and Diagnosis.
- EPSRC (Engineering and Physical Sciences Research Council): Sentiment- Automated surgical skill assessment.
- EPSRC (Engineering and Physical Sciences Research Council): Daphne: Automated filtering of normal images in DR screening programme.
- The Leverhulme Trust: Morphometric Herbarium Image Data Analysis (Morphidas).
- The Royal Surrey County Hospital: Mammography quality assurance using visual information processing.
- Royal Academy of Engineering: Vision and graphic research.
- Federal Innovative Fund: Artful Eyes.
- University of Cambridge: Pathological image analysis for visual hospital.
COM2028 Introduction to AI
COM3025 Deep Learning and Advanced AI
About 100 refereed papers were published. Highlights below include mostly those from recent years:
- Al Turk L; Georgieva D; Alsawadi H; Wang S; Krause P; Alsawadi H; Alshamrani A; Saleh G M; Tang H L, Learning to Discover Explainable Clinical Features With Minimum Supervision, Translational Vision Science & Technology January 2022, Vol.11, 11.
- Mei X, Huang Q, Liu X, Chen G, Wu J, Wu Y, Zhao J, Li S, Ko T, Tang H L, Shao X, Plumbley M D, Wang W, An Encoder-Decoder Based Audio Captioning System With Transfer and Reinforcement Learning, DCASE-21.
- Liu X, Huang Q, Mei X, Ko T, Tang H L, Plumbley M D, Wang W, A Contrastive Loss for Audio Captioning, DCASE-21
- Quinn N, Brazionis L, Zhu B, Ryan C, Tang* H L, Peto T, A Jenkins, Facilitating diabetic retinopathy screening using automated retinal image analysis in less-advantaged communities or under-resourced settings, Diabetic Medicine
- Huang, Q., Ko, T., Tang, H.L., Liu, X., Wu, B. (2021) Token-Level Supervised Contrastive Learning for Punctuation Restoration. Proc. Interspeech 2021, 2012-2016, doi: 10.21437/Interspeech.2021-661
- Al Turk L, Wawrzynski J, Wang S , Krause P, Saleh G M, Alsawadi H, Alshamrani A Z, Peto T, Bastawrous A, Li J, and Tang H L, Automated Feature-Based Grading and Progression Analysis of Diabetic Retinopathy (Running title: Feature based detection of diabetic retinopathy), Eye, Nature.
- Al Turk L; Wang S; Krause P; Wawrzynski J; Saleh G M.; Alsawadi H; Alshamrani A Z; Peto T; Bastawrous A; J Li; Tang H L, Evidence Based Prediction and Progression Monitoring on Retinal Images from Three Nations, Translational Vision Science & Technology August 2020, Vol.9, 44. doi:https://doi.org/10.1167/tvst.9.2.44
- Hingley-Wilson S M., Ma N, Hu Y, Casey R, Bramming A, Curry R J., Tang H L, Wu H, Butler R E., Jacobs Jr W R., Rocco A, and McFadden J, Loss of phenotypic inheritance associated with ydcI mutation leads to increased frequency of small, slow persisters in Escherichia coli, PNAS, first published February 6, 2020 https://doi.org/10.1073/pnas.1914741117.
- Almani N and Tang L, Deep Attention-Based Review Level Sentiment Analysis for Arabic Reviews, 6TH INTERNATIONAL CONFERENCE ON DATA SCIENCE AND MACHINE LEARNING APPLICATIONS, 4-5 March, Prince Sultan University, Riyadh, KSA
- Almisbahi H. O., Faux D. A., Tang L. H., Abulkhair M. F., Visualizing molecular phonons using eigenvectors with smallest eigenvalues of the atomic trajectories", Computational Materials Science, 2019, https://doi.org/10.1016/j.commatsci.2019.01.002
- Hamill, B; Tang, HL; Sivaraman, N; Peto, T, The Comparison Between An Automated Reading and Human Grading of Images From a Handheld Wide Field Imaging Device, European Journal of Ophthalmology, Volume: 29 Issue: 3, MAY 2019.
- Al Turk L, Wang S, Krause P, Alsawadi H, Alshamrani A. Z, Peto T, Bastawrous A, Huang W, and Tang H. L, Automated Retinal Image Reading and Progression Analysis, European Journal of Ophthalmology, 2018.
- Balal S, Smith P, Bader T, Tang H, Sullivan P, Thomsen A. S, Carlson T, Saleh G, Computer analysis of individual cataract surgery segments in the operating room, Eye, Nature, volume 33, pages 313–319 (2019).
- Balntas V, Tang L, Mikolajczyk K, 2018, Binary Online Learned Descriptors, IEEE Transactions on Pattern Analysis and Machine Intelligence.
- Day A., Smith P, Tang H. L., Aiello F, Hussain B, Maurino V, Marshall J, Saleh G. S., Surgical efficiency in femtosecond laser cataract surgery compared to phacoemulsification cataract surgery: a case control study, BMJ Open.
- Hu Y, Wang S, Ma N, Hingley-Wilson S, Rocco, A, McFadden J, H. L. Tang, "Trajectory Energy Minimisation for Cell Growth Tracking and Genealogy Analysis", Royal Society Open Science.
- Thomsen A S, Smith P, Morten la Cour Y S,, Tang L, Saleh G M., Konge L, High correlation between performance on a virtual-reality simulator and real-life cataract surgery, Acta Ophthalmologica. 2016 Sep 29. doi: 10.1111/aos.13275.
- Hansen M B., Tang HL, Wang S, Al Turk L, Piermarocchi R, Speckauskas M, Hense H-W, Leung I and Peto T, Automated detection of Diabetic Retinopathy in Three European Populations, Journal of Clinical & Experimental Ophthalmology, cited as: Hansen et al., J Clin Exp Ophthalmol 2016, 7:4, DOI: 10.4172/2155-9570.1000582.
- Din N, Smith P, Emeriewen K, Sharma A, Jones S, Tang H, Sullivan P, Caputo S and Saleh G M., Man vs Machine: Software training for surgeons -an objective evaluation of human and computer-based training tools for cataract surgical performance.", Journal of Ophthalmology, vol. 2016, Article ID 3548039, 2016. doi:10.1155/2016/3548039.
- Saleh G M., Wawrzynski J, Caputo S, Peto T, Al turk L, Wang S, Hu Y, Cruz L. D, Smith P and Tang H, An automated detection system for microaneurysms that is effective across different racial groups, Journal of Ophthalmology.
- Wang S; Tang, H L; Al turk, L; Hu, Y; Sanei, S; Saleh, G; Peto, T, Localising Microaneurysms in Fundus Images Through Singular Spectrum Analysis, IEEE Transactions on Biomedical Engineering, Print ISSN: 0018-9294, Online ISSN: 1558-2531, Digital Object Identifier: 10.1109/TBME.2016.2585344, 2016 Jun 27.
- Alghamdi H S, Tang H L, Waheeb S A., and Peto T, Automatic Optic Disc Abnormality Detection in Fundus Images: A Deep Learning Approach, 19th International Conference on Medical Image Computing & Computer Assisted Intervention, MICCAI 2016.
- Safaei A, Tang H L, Sanei S (2016), Real Time Search Free Multiple License Plate Recognition via Likelihood Estimation of Saliency, Computers and Electrical Engineering.
- Safaei A, Tang HL, Sanei S, Incorporating Negentropy in Saliency-based Search Free Car Number Plate Localization, 2016 International Conference on Digital Signal Processing (DSP)
- Safaei A, Tang HL, Sanei S (2016) Robust Search-Free Car Number Plate Localization Incorporating Hierarchical Saliency. Journal of Computer Science & Systems Biology, 9:093-103. doi:10.4172/jcsb.1000225
- Wawrzynski J R, Smith P, Tang L, Hoare T, Caputo S, Marshall J, Tsatsos M, Saleh G M, Tracking camera control in endoscopic dacryocystorhinostomy surgery., Clinical Otolaryngology, 2015 Apr 8. PMID: 25858299.
- Balntas V, Johns E, Tang L, Mikolajczyk K, PN-Net: Conjoined Triple Deep Network for Learning Local Image Descriptors, arXiv:1601.05030 [cs.CV].
- Alghmdi H, Tang H L, Hansen M, O'Shea A, Al turk L, Peto T, Measurement of Optical Cup to Disc Ratio in Fundus Images for Glaucoma screening, International Workshop on Computational Intelligence for Multimedia Understanding IWCIM 2015, Prague, Czech Republic.
- Peto T, Saleh G M, Caputo S, Al turk L I, Wang S, Hu Y, Tang H L, The Application of Machine Learning to the Automated Detection of Microaneurysms in Different Ethnic Group with Diabetic Retinopathy, European Journal of Ophthalmology.
- Balntas V, Tang L, Mikolajczyk K, “BOLD - Binary Online Learnt Descriptor for efficient image matching”, CVPR2015, June 7-12 2015, Boston, Massachusetts.
- Alghamdi H. S. Tang L, Jin Y, Ensemble Learning Optimization for Diabetic Retinopathy Image Analysis, 10th International Conference on Computer Vision Theory and Applications, 11-14 March 2015, Berlin, Germany.
- Balntas V, Tang L, Mikolajczyk K, Improving object tracking with voting from false positive detections, 22nd International Conference on Pattern Recognition (ICPR), 24-28 August 2014 Stockholm, Sweden.
- Safaei A, Tang HL. and Sanei S, Search-free license plate localisation based on Saliency and local variance estimation. The 7th International Conference on Machine Vision (ICMV 2014).
- Tang HL, Goh J, Peto T, Ling BW-K, Al turk L, et al. (2013) The Reading of Components of Diabetic Retinopathy: An Evolutionary Approach for Filtering Normal Digital Fundus Imaging in Screening and Population Based Studies. PLoS ONE 8(7): e66730. doi:10.1371/journal.pone.0066730.
- Smith P, Tang L, Balntas V, Young K, Athanasiadis Y, Sullivan P, Hussain B and Saleh GM, “PhacoTracking” An Evolving Paradigm in Ophthalmic Surgical Training, JAMA Ophthalmol. 2013;131(5):659-661. doi:10.1001/jamaophthalmol.2013.28.
- Corney DPA, Tang HL, Clark JY, Hu Y, Jin J (2012) Automating Digital Leaf Measurement: The Tooth, the Whole Tooth, and Nothing but the Tooth. PloS ONE 7(8): e42112. doi:10.1371/journal.pone.0042112.
- Clark J, Corney D and Tang L (2012), Automated Plant Identification using Artificial Neural Networks, the 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, May 9-12, 2012 San Diego, California.
- Subramaniam S. R, Georgakis A, Ling B.W.K, Goh J, Tang H.L., Peto T. and Saleh G., Optimal and Simultaneous Designs of Hermitian Transforms and Masks for Reducing Intraclass Separations of Feature Vectors for Anomaly Detection of Diabetic Retinopathy Images, IEEE, IET 8th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP 2012), 18-20 July 2012, Poznan, Poland.
- Goh J, Tang L, Peto T and Saleh G, An Evolutionary Approach for Determining Hidden Markov Model for Medical Image Analysis, the 2012 IEEE Congress on Evolutionary Computation, 11-15 June 2012, Brisbane, Australia.
- Corney DPA, Clark JY, Tang HL, Wilkin P, Automatic Extraction of Leaf Characters from Herbarium Specimens, TAXON 61 (1), February 2012: 231–244.
- Tang H. L., Peto T., Goh J., Jin Y., Chuluunkhuu C., Filtering Normal Diabetic Retinopathy Images through Evolutionary Computation, European Journal of Ophthalmology, Vol.21, No.3, May-June 2011.
- Baldas, V., Tang, L., Bountris, P., Saleh, G., & Koutsouris, D. (2010). A real-time automatic instrument tracking system on cataract surgery videos for dexterity assessment. Proceedings of the IEEE/EMBS Region 8 International Conference on Information Technology Applications in Biomedicine, ITAB.
- Goh, J., Tang, L., Saleh, G., Al Turk, L., Fu, Y., & Browne, A. (2009). Filtering Normal Retinal Images for Diabetic Retinopathy Screening Using Multiple Classifiers. In 2009 9TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND APPLICATIONS IN BIOMEDICINE (pp. 609-612). Larnaka, CYPRUS: IEEE.
- Chen, L., & Tang, H. L. (2004, February 19). Improved computation of beliefs based on confusion matrix for combining multiple classifiers. ELECTRON LETT, 40(4), 238-239. doi:10.1049/el:20040176.
- Tang, H. L., Hanka, R., & Ip, H. (2003). Histological image retrieval based on semantic content analysis. IEEE Transactions On Information Technology In Biomedicine, 7(1), 26-36. doi:10.1109/TITB.2003.808500, MARCH 2003.
- Tang, L. H. Y., Hanka, R., Ip, H., Cheung, K., & Lam, R. (2000). Semantic query processing and annotation generation for content-based retrieval of histological images. Proceedings of SPIE - The International Society for Optical Engineering, 3980, 366-375. (Cum Laude Award).
There are at least further 54 refereed papers published including 17 publications on my early work in natural language processing and machine translation.