• Data Mining, Optimization Theory
• Unsupervised Learning
• Supervised Learning
• Image Processing
• Medical Image Processing
• Pattern Recognition

• Best Innovation & research (Postgraduate & Open) Silver Award, awarded by Hong Kong ICT Awards 2013
• Best Innovation & Research (Postgraduate & Open) and Special Mention (Small Project), awarded by Hong Kong ICT Awards 2013
• Ph.D Colloquia Series: Certificate of Merit, awarded by ICMLC 2007
• Who’s Who, awarded by Marquis Who's Who 2009 and 2010

• R & D Consultant, City Image Technology Limited (6/2013 to now)
• Program Committee, ICMLC (2006–2013)
• Program Committee, Asia-Pacific Workshop on VIP (Visual Information Processing) 2005
• Reviewer (Conference), KES2006 General Track
• Reviewer (Conference), IEEE System, Man and Cybernetics (SMC) (2006,2008,2009)
• Reviewer (Journal), IEEE Transactions on Signal Processing Letters (2014)
• Reviewer (Journal), IEE Proc. Vision, Image & Signal Processing
• Reviewer (Journal), IEEE on Medical Imaging (2009, 2011)
• Reviewer (Journal), Computers in Biology and Medicine (2010 – 2013)
• Session Chair, International Conference on Pattern Recognition (ICPR) 2006
• Session Chair, International Conference on Machine Learning and Cybernetics (ICMLC)2007
• Session Chair, Digital Image Computing: Techniques and Applications (DICTA) 2009

..........Journal Articles..........

1. Benson S. Y. Lam and Alan W. C. Liew, “A Fast Binary Quadratic Programming Solver based on Stochastic Neighborhood Search,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 44, Issue 1, pp. 32-49, doi: 10.1109/TPAMI.2020.3010811, 2022.
2. Benson S. Y. Lam, M. F. Cheung and W. H. Lo, “What Matters Most in the Responses to Political Campaign Posts on Social Media: The Candidate, Message Frame, or Message Format?” Computers in Human Behavior, Vol. 121, pp. 106800, doi: 10.1016/j.chb.2021.106800, 2021.
3. S. K. Choy, Carisa K. W. Yu, Tanki C. L. Lee, Benson S. Y. Lam and Catherine Y. W. Wong, “A Two-stage Variational Jump Point Detection Algorithm for Real Estate Analysis,” Land Use Policy, Vol. 111, pp. 105687, doi: 10.1016/j.landusepol.2021.105687, 2021.
4. Amanda M. Y. Chu, Connie K. W. Liu, Mike K. P. So and Benson S. Y. Lam, “Factors for Sustainable Online Learning in Higher Education during the COVID-19 Pandemic,” Sustainability, Vol. 13, Issue 9, pp. 5038, doi: 10.3390/su13095038, 2021.
5. M. F. Cheung, Benson S. Y. Lam and Brian So, “Who Leads the IPOs News: Intermedia Agenda-setting in a Routinised and Standardised News Context,” Journalism Studies, Vol. 21, Issue 12, pp. 1681-1704, doi: 10.1080/1461670X.2020.1788974, 2020.
6. Benson S. Y. Lam, Amanda M. Y. Chu and H. Yan, “Statistical Bootstrap-based Principal Mode Component Analysis for Dynamic Background Subtraction,” Pattern Recognition, Vol. 100, pp. 107153, doi: 10.1016/j.patcog.2019.107153, 2020.
7. Amanda M. Y. Chu, Benson S. Y. Lam, Agnes Tiwari, Mike K. P. So, “An Empirical Study of Applying Statistical Disclosure Control Methods to Public Health Research,” International Journal of Environmental Research and Public Health, doi: 10.3390/ijerph16224519, 2019.
8. W. H. Lo, Benson S. Y. Lam and M. F. Cheung, “The Dynamics of Political Elections: A Big Data Analysis of Intermedia Framing Between Social Media and News Media,” Social Science Computer Review, Vol. 39, Issue 4, pp.627-647, doi: 10.1177/0894439319876593, 2019.
9. Benson S. Y. Lam and S. K. Choy, “A Trimmed Clustering- Based l1-Principal Component Analysis Model for Image Classification and Clustering Problems with Outliers,” Applied Sciences, Vol. 9(8), 1562, 2019.
10. S. K. Choy, Benson S. Y. Lam, K. W. Yu, W. Y. Lee and K. T. Leung, “Fuzzy Model-based Clustering and Its Application in Image Segmentation”, Pattern Recognition, vol. 68, pp. 141-157, 2017.
11. Benson S. Y. Lam, Carisa. K. W. Yu, S. K. Choy, Jacky, K. T. Leung, “Jump Point Detection Using Empirical Mode Decomposition”, Land Use Policy, Vol. 58, pp. 1–8, 2016.
12. Benson S. Y. Lam,YongshengGao, Alan Liew,“General Retinal Vessel Segmentation Using Regularization-based Multi-concavity Modeling,” IEEE Transactions on Medical Imaging,Vol. 29, pp. 1369-1381, 2010.
13. Benson S. Y. Lam and Hong Yan,“A Novel Vessel Segmentation Algorithm for Pathological Retina Images Based on the Divergence of Vector Fields,” IEEE Transactions on Medical Imaging,Vol. 27, pp.237-246, 2008.
14. Benson S. Y. Lam, Alan Wee-Chung Liew, David K. Smith and Hong Yan, “A Regularized Clustering Algorithm Based on Calculus of Variations,” Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, doi 10.1007/s11265-007-0119-9, Aug 2007 (online).
15. Benson S. Y. Lam and Hong Yan,“A Curve Tracing Algorithm Using Level Set Based Affine Transform,” Pattern Recognition Letters, Volume 28, Issue 2, pp. 181-196, 2007.
16. Benson S. Y. Lam and Hong Yan,“Subdimension-based Similarity Measure for DNA Microarray Data Clustering,” Virtual Journal of Biological Physics Research(http://scitation.aip.org/dbt/dbt.jsp?KEY=VIRT02&Volume=12&Issue=8), Volume 12, Issue 8, 74041906, 2006.
17. Benson S. Y. Lam and Hong Yan,“Subdimension-based Similarity Measure for DNA Microarray Data Clustering,”Physical Review E, 74, 041906 (2006).
18. Benson S. Y. Lam and Hong Yan, “A New Curve Tracing Algorithm Based on a Minimum Spanning Tree Model and Regularized Fuzzy Clustering,” Optical Engineering, Volume 45, pp. 2006.
19. Benson S. Y. Lam and Hong Yan, “Assessment of Microarray Data Clustering Results Based on a New Geometrical Index for Cluster Validity,” Soft Computing - A Fusion of Foundations, Methodologies and Applications, Volume 11, Issue 4, pp. 341-348, 2006.
20. S. Y. Lam and C. S. Tong, “Enhanced Snake Algorithm by Embedded Domain Transformation,” Pattern Recognition, Vol. 39, pp. 1566-1574, Sept 2006.
21. S. Y. Lam and C. S. Tong, “Conformal Snake Algorithm for Contour Detection,” Electronics Letters, Vol. 38, pp. 452-453, May 9, 2002.

..........Conference Proceedings & Book Chapters..........

1. S. Y. Lam, Who Leads the IPOs News: Intermedia Agenda-setting in a Routinised and Standardised News Context, ICA 2020.
2. Y. Lam, What Matters More in Political Expressions in Social Media Campaigns: Candidates, Message Frames or Forms?, ICA 2020.
3. Brian So, M. F. Cheung and S. Y. Lam, “Regulation, routinization and standardization: Challenges to the professionalism of financial journalism in the context of IPO news,” International Association for Media and Communication Research, IAMCR 2019.
4. W. H. Lo, M. F. Cheung and S. Y. Lam, “Not all message frames and forms are the same: What matters most in political expressions in social media campaigns,” International Conference on Research in Advertising (ICORIA), 2019.
5. W. H. Lo, M. F. Cheung and S. Y. Lam, Who has a say in political election? Framing in the Era of Big Data, The 68th Annual Conference of International Communication Association (ICA), 2018.
6. Benson Y. Lam, “Binary Quadratic Program Algorithms for Large Scale Problems,” 1st International Conference on Econometrics and Statistics (EcoSta), June 15-17, 2017.
7. Zhu, W. Y. Lee, S. K. Choy, S. Y. Lam and K. W. Yu, “Systemic Weather Risk and Agricultural Insurance Pricing,” 21st International Congress on Insurance: Mathematics and Economics, Vienna, July 3-5, 2017.
8. Benson S. Y. Lam and S. K. Choy, "K-Medians Clustering Based -PCA Model," ICASSP 2015 (Rank A Conference), Accepted for presentation
9. Benson S. Y. Lam, YongshengGao and Alan Liew, “Optimizing Sharpness Measure for Bright Lesion Detection in Retinal Image Analysis,” Digital Image Computing: Techniques and Applications (DICTA), pp. 19-24, 2009.
10. Yi Wang, Benson S. Y. Lam, and Hong Yan, “A Sub-dimension Based Probabilistic Neural Network for Occlusion Classification,” InternationalMulitConference of Engineers and Computer Scientists (IMECS 2008), 2008.
11. Benson S. Y. Lam and Hong Yan, “Robust Clustering Algorithm for High Dimensional Data Classification based on Multiple Supports,” International Joint Conference on Neural Networks (IJCNN 2008), pp. 1969-1976, 2008.
12. Benson S. Y. Lam and Hong Yan, “A Novel Dimensionality Reduction Method for Pattern Classification,” International Conference on Systems, Man and Cybernetics, pp. 1125-1129, 2007.
13. Benson S. Y. Lam and Hong Yan, “An Effective Method ForClassification Of High Dimensional Data,” International Conference on Machine Learning and Cybernetics, pp. 2713-2718, 2007.
14. Benson S. Y. Lam and Hong Yan, “Improved Clustering Algorithm Based on Calculus of Variation,” ICPR, pp. 900-903, 2006.
15. B. S. Y. Lam and Hong Yan, “Blood Vessel Extraction Based on Mumford-Shah Model and Skeletonization,” International Conference on Machine Learning and Cybernetics, pp. 4227-4230, 2006.
16. B. S. Y. Lam and Hong Yan, “A New Cluster Validity Index for Data with Merged Clusters and Different Densities,” IEEE Int. Conf. on Systems, Man and Cybernetics, pp. 798-803, 2005.
17. B. S. Y. Lam and Hong Yan, “A Curve Tracing Algorithm Using Level Set Based Affine Transforms,” IEEE Int. Conf. on Systems, Man and Cybernetics, pp. 2667-2672, 2005.
18. B. S. Y. Lam and Hong Yan, “Cluster Validity For DNA Microarray Data Using a Geometrical Index,” Proc. Int. Conf. Machine Learning and Cybernetics, pp. 3333-3339, 2005.
19. B. S. Y. Lam and Hong Yan, “A New Similarity Measure for Microarray Data Analysis,”International Symposium on Intelligent Signal Processing and Communication Systems, pp. 461-464, 2005.
20. B. S. Y. Lam and Hong Yan, “Robust Clustering Algorithm for Suppression of Outliers”, International Symposium on Intelligent Multimedia, Video & Speech Processing, pp. 619-694, 2004.
21. B. S. Y. Lam and Hong Yan, “Complex Curve Tracing Based on a Minimum Spanning Tree Model and Regularized Fuzzy Clustering,”IEEE International Conference on Image Processing, pp. 2091-2094, 2004.
22. S. Y. Lam and C. S. Tong, “Advances in Snake Algorithms,” International Conference on Scientific Computing and Partial Differential Equations, December 12-15, 2002.
23. S. Y. Lam and C. S. Tong,“Is Snake Impossible to Detect Concave Parts?,” First SIAM Conference on Imaging Science, March 4-6, 2002.

• (Research Matching Grant Scheme) HK$7,008,344. "Applications of SAS Viya in Big Data Analytics," funded by the University Grants Committee (UGC) 2019/2020. (Co-PI)
• (UGC/FDS14/P04/17) HK$476,200. “Supervised Dimensionality Reduction with Unsupervised Learning: Theory and Applications,” funded by the University Grants Committee (UGC) 2017/2018. (PI)
• (UGC/FDS14/H17/17) HK$441,700. “Agenda-building in IPOs – Exploring the relationship between public relations efforts and financial news coverage,” funded by the University Grants Committee (UGC) 2017/2018. (Co-I)
• (UGC/IIDS14/P01/17) HK$403,750. “Recent Developments in Business Analytics and New Research Directions,” funded by the University Grants Committee (UGC) 2017/2018.
• (UGC/IDS14/16) HK$6,998,000. “Establishment of a Deep Learning Research & Application Centre,” funded by the University Grants Committee (UGC) 2016/2017.
• (UGC/FDS14/P04/15) HK$870,550. “Fuzzy Generalised Gaussian Density Segmentation Model: Mathematical Analysis and Applications,” funded by the University Grants Committee (UGC) 2015/2016. (Co-I)
• (UGC/FDS14/E02/14) HK$573,620. “Model-based Unsupervised Image Segmentation,” funded by the University Grants Committee (UGC) 2014/2015.  (Co-I)
• (UGC/FDS14/E03/14) HK$989,897. "Data Functional Modelling with Outliers," funded by the University Grants Committee (UGC) 2014/2015. (PI)
• (E/P002/13) HK$2,053,570. “Professional high quality 2D to 3D Conversion System,” funded by - Small Entrepreneur Research Assistance Programme (SERAP), Hong Kong Government 2013/2014.

• Sing Tao Daily (恒管語絲): 標題:零一個和我們生活息息相關的數字, 2014年10月07日
• Sing Tao Daily (恒管語絲): 標題:零一個被忽略的數字, 2014年06月20日