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Dr Sin Wee Lee

Senior Lecturer ; Programme Leader Programme Leader for BSc (Hons) Computer Science and BSc (Hons) Software Engineering ; Deputy Quality Leader for School of Architecture, Computing and Engineering ; Academic Link tutor for Collaboration

I am a Senior Lecturer, Programme Leader and Deputy Quality Leader of the School of Architecture, Computing and Engineering.  My aim is to develop and deliver high quality programmes that integrate all the expertise available in the school to enable students to have the best learning experience and well prepared for employment. My academic and research interest include Data Mining, Artificial Intelligence and Machine Learning. 

  • EB 1.104, Dockland Campus
    School of Architecture Computing and Engineering (ACE)
    University of East London
    4-6 University Way
    London
    E16 2RD
  • s.w.lee@uel.ac.uk +442082232871
    Sin Wee’s expertise includes Artificial Intelligence, Intelligent Data Analysis, Green IT and Innovative Higher Education Technologies


    Prince 2 Practitioner 

    Overview




    Sin Wee’s main areas of expertise are in the field of Artificial Intelligence and Artificial Neural Networks (ANN), Green IT and Innovative Higher Education Technologies; focusing on innovative applications in Pattern Recognition, Natural Language Processing, Intelligence Data Analysis, Green IT policy and sustainability in Higher Education.

    He is well experienced in developing and implementing research strategies, managing research and education collaborations either between academic, with academic, or academic with industry; locally and internationally. During his professional career, he has also acquired an in depth skill in generating reports and evaluations on progress and on end results of the development and implementation of research strategies and latest innovation in the field of Artificial Intelligence and Artificial Neural Networks.

    During his PhD, Sin Wee developed a new self-optimising reinforcement learning algorithm, known as
    snap-drift, when incorporated into a modular neural network system, is capable of rapidly adapting to discover provisional solutions that meet criteria imposed by a changing environment. This is analogous to humans optimising selection according to the options available in the surrounding environment.
    Other scholarly activities

    Reviewer, Software Quality Journal
    Reviewer, Journal of Neurocomputing
    Reviewer, Journal of Neural Computing and Applications
    Organising Committee for EANN
    Programme Committee for International Conference on Neural Computation (ICNC)


    Collaborators

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    Research

    Keynotes Lee, S. W. (2008). "Snap-Drift Algorithm". Doctoral Symposium on Research in Computer Science, University of Central Punjab, August 9 -10.

    Palmer-Brown, D.; Lee S. W. (2005). “Continuous Reinforced Snap-Drift Learning in a Neural Architecture for Proxylet Selection in Active Computer Networks.” (Invited paper). International Journal on Simulation: Systems, Science and Technology, vol. 6, no. 9, pp. 11 – 21.

    Donelan, H.; Pattinson, C.; Palmer-Brown D.; Lee S. W. (2005). “The Analysis of Network Manager’s Behaviour using a Self-Organising Neural Networks.” (Invited paper). International Journal on Simulation: Systems, Science and Technology, vol. 6, no. 9, pp. 22 – 32.

    Lee, S. W.; Palmer-Brown, D.; Roadknight C. M. (2004). “Performance-guided Neural Network for Rapidly Self-Organising Active Network Management.” Neurocomputing, Elsevier Science, Netherlands, Vol. 61, pp. 5 – 20.

    Peer-Reviewed Conference Papers: Lau, B. T.; Wong, M. L. D.; Naeem, U.; Lee, S. W. (2013). “An Indoor Prototype Framework for Recognition of Activities of Daily Life”, The 7th Conference on Rehabilitation Engineering and Assistive Technology Society of Korea 2013 (Seoul, Korea), 1 – 2 November.

    Saffieddine, F. Lee, S. W. (2013). "Green Module for Sustainability in Higher Education", 7th International Technology, Education and Development Conference, (Valencia, Spain), 4th - 7th March.

    Guo, R. S.; Palmer-Brown, D.; Lee, S. W.; Cai, F. F. (2012)."Effective Diagnostic Feedback for Online Multiple-Choice Questions". 8th Conference in Artificial Intelligence Applications and Innovations (Haikidiki, Greece), 27th - 30th September, pp. 316-326.

    Guo, R. S.; Lee, S. W.; Palmer-Brown, D. (2012). "Effective Diagnostic Feedback Methods for Online Multiple-Choice Questions", 6th Conference in Advances in Computing and Technology (London, United Kingdom), 26th Jan, pp. 68-76.

    Imran, A.; Jahakhani, H.; Lee, S. W.; Al-Nemrat, A. (2011). "Education, Training and Awareness (ETA) Four Dimensional Cybercrime Prevention Model". Kaspersky's IT Security for the Next Generation - European Cup (Erfurt, Germany), 28th-30th Jan.

    Matieni, X.; Dodds, S.; Lee, S. W. (2011) "Direct state feedback optimal control of a double integrator plant implemented by an artificial neural network", Advances in Computing and Technology (London, United Kingdom), pp.234-240.

    Xavier, M.; Dodds, S. and Lee, S. W. (2010). "Closed-Loop Control using a Backpropagation Algorithm: A Practicable Approach for Energy Loss Minimisation in Electrical Drives". 5th Conference in Advances in Computing and Technology (London, United Kingdom, 27th Jan), pp. 72 - 78.

    Invited Talks 2013 "Robust Recognition of Activities of Daily Living using Intelligent Reasoning", Swinburne University of Technology, Sarawak, Malaysia.

    Beqiri, E.; Lee. S. W.; Draganova, C. and Palmer-Brown, D. (2010). "A Neural Network Approach for Intrusion Detection Systems", 5th Conference in Advances in Computing and Technology (London, United Kingdom, 27th Jan), pp. 209 -217.

    Draganova, C.; Kans, A.; Lee, S. W. (2009). "Intelligent Feedback to Enhance the Student Learning Experience", UEL Conference in Learning, Teaching & Assessment (London, United Kingdom).

    Draganova, C.; Palmer-Brown, D.; Lee, S. W. (2009). “Guided Learning via Diagnostic Feedback to Question Responses", The 14th ACM–SIGCSE Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE'09) (Paris, France, 3rd - 8th July). pp. 362-372.

    Palmer-Brown, D.; Draganova, C.; Lee, S.W. (2009). "Snap-Drift Neural Network for Selecting Student Feedback", The International Joint Conference on Neural Networks (IJCNN’2009) (Atlanta, Georgia, 14th - 19 June), pp. 391-398.

    Lee, S. W.; Palmer-Brown, D; Draganova, C.; Kretsis, M.; Preston, P. (2009). "Question Response Grouping for on-line Diagnostic Feedback", 4th Conference in Advances in Computing and Technology (London, United Kingdom, 27th January), pp. 68-76.

    Walcott, T. H.; Palmer-Brown, D.; Lee, S.W. (2008). “Creating Intelligent Markets for SMEs using the Snap-Drift Algorithm: A Higher Education College Perspective”, 11th Multiconference on Information Society, pp. 105-108.

    Walcott, T.H; Palmer-Brown, D.; Lee, S.W. (2008). "Early SME Market Prediction using USDNN", In Proceedings of the International Conference of Computational Intelligence and Intelligent Systems (ICCIIS'2008),(London, United Kingdom, July 2-4,2008)., pp.72-75.

    Lee, S. W.; Palmer-Brown, D.; Draganova, C. (2008). “Diagnostic Feedback by Snap-drift Question Response Grouping”, In proceedings of The 9th WSEAS International Conference on Neural Networks (NN'08) (Sofia, Bulgaria, May 2-4, 2008), pp. 208-214.

    Palmer-Brown, D.; Kang, M.; Lee, S. W. (2008). “Meta-Adaptation: Neurons that Change their Mode”, In proceedings of The 9th WSEAS International Conference on Neural Networks (NN'08) (Sofia, Bulgaria, May 2-4, 2008), pp. 155-166.

    Lee, S. W. and Palmer-Brown, D. (2007). "Feature Discovery in Speech using Snap-Drift Neural Networks", 2nd Conference in Advances in Computing and Technology (London, United Kingdom, 23th January), pp. 61-70.

    2013 "Adaptive Learning Algorithm for e- learning", Tunku Abdul Rahman College (TARC), Malaysia.

    Walcott, T.; Palmer-Brown, D.; Godfried, W.; Mourathidis, H.; Lee, S. W. (2007). "An Assessment of Neural Network Algorithms that could aid SME Survival", 2nd Conference in Advances in Computing and Technology (London, United Kingdom, 23th January), pp.120-127.

    Ekpenyong, F.; A. Brimicombe; D. Palmer-Brown and S. W. Lee (2007). “Automated Updating Of Road Network Databases: Road Segment Grouping Using Snap-Drift Neural Network", 2nd Conference in Advances in Computing and Technology (London, United Kingdom, 23th January), pp. 160-167.

    Lee, S. W. and D. Palmer-Brown (2006). "Phonetic Feature Discovery in Speech using Snap-Drift." International Conference on Artificial Neural Networks (ICANN'2006) (Athen, Greece, 10th - 14th September 2006), S. Kollias et al. (Eds.): ICANN 2006, Part II, LNCS 4132, pp. 952 – 962.

    Lee, S. W. and D. Palmer-Brown (2006). “Modal Learning in A Neural Network.” 1st Conference in Advances in Computing and Technology (London, United Kingdom, 24th January), pp. 42 - 47.

    Lee, S. W. and D. Palmer-Brown (2005). “Phrase Recognition using Snap-Drift Learning Algorithm.” The International Joint Conference on Neural Networks (IJCNN’2005) (Montreal, Canada, 31st July – 4th August), Vol. 1, pp. 588-592.

    Lee, S. W.; D. Palmer-Brown and C. M. Roadknight. (2004). “Snap-drift: Performance-guided Neural Network for Continuous Learning.” Special House of Commons’ Reception for Younger Researchers, House of Commons (London, UK, 15th September).

    Lee, S. W.; D. Palmer-Brown and C. M. Roadknight. (2004). “Continuous Reinforced Snap-Drift Learning in a Neural Architecture for Proxylet Selection in Active Computer Networks.” (Invited paper). In Proceedings of The 18th European Simulations Multiconference (ESM’2004) (Magdeburg, Germany, 13th – 16th June), pp. 136 – 142.

    Donelan, H.; C. Pattinson; D. Palmer-Brown and S. W. Lee. (2004). “The Analysis of Network Manager’s Behaviour using a Self-Organising Neural Networks.” In Proceedings of The 18th European Simulations Multiconference (ESM’2004) (Magdeburg, Germany, 13th – 16th June), pp. 111 – 116.

    Lee, S. W.; D. Palmer-Brown and C. M. Roadknight. (2004). “Reinforced Snap-Drift Learning for Proxylet Selection in Active Computer Networks.” In Proceedings of the International Joint Conference on Neural Networks (IJCNN’2004) (Budapest, Hungary, 25th – 29th July), Vol. 2, pp. 1545 – 1550.

    2013 "Machine Learning, Reality or Fiction?", Kuala Lumpur Metropolitan University, Malaysia.

    2013 "Introduction to Data Mining", Kuala Lumpur Infrastructure University, Malaysia

    Book Chapters Lee, S. W.; Palmer-Brown D.; Tepper, J.; Roadknight. C. M. (2002). “Performance-guided Neural Network for Rapidly Self-Organising Active Network Management.” In Soft Computing Systems: Design, Management and Applications, A. Abraham J. Ruiz-del-Solar and M. Köppen (Eds.). IOS Press, Amsterdam, pp. 21 – 31.

    Peer-Reviewed Journal Papers Naeem, U.; Azam, M.A,; Lee, S. W.; Wong, M.L.; Tawil, A. R.; Bashroush, R. (2013). "Activities of Daily Life Recognition and Intention Analysis using Process Representation Modelling", IEEE Journal of Biomedical and Health Informatics (J-BHI). (Submitted)

    Guo, R. S.; Palmer-Brown, D.; Lee, S. W.; Cai, F. F. (2013)."Effective Diagnostic Feedback for Online Multiple-Choice Questions". Artificial Intelligence Review, Springer. Matieni, X.; Dodds, S.; Lee, S. W. (2012). "Investigation by Simulation of Closed-loop Optimal Control Law Implementation using Artificial Neural Network", International Review on Modelling and Simulations, vol. 5, no. 5, pp. 2119 - 2127.

    Palmer-Brown, D.; S. W. Lee.; Draganova, C.; Kang, M.(2009). "Modal Learning Neural Networks." WSAES Transactions on Computers, vol. 8, no. 2, pp. 222 - 236.

    Publications




    Programmes

    Extended Degree in BIT
    Professional Doctoral
    BSc (Hons) Software Engineering

    Modules

    Data Mining and Data Analysis
    Introduction to Software Design
    Mathematical Optimisation
    Applied Research Tools and Techniques

    Teaching