James Swee Chuan Tan

Associate Professor James Tan Swee Chuan

Head, Business Analytics Programme

School of Business

Tel: +65 6248 1618

Email: amFtZXN0YW5zY0BzdXNzLmVkdS5zZw==

Educational Qualifications

  • 2009
    PhD (Information Technology), Monash University
  • 2005
    MIT, Monash University
  • 1995
    BIT, University of Southern Queensland

Academic and Professional Experience

  • 2019 - Present
    Head of Programme, School of Business
  • 2015 - 2018
    Deputy Head of Programme, School of Business
  • 2013 - 2015
    Senior Lecturer, School of Business
  • 2010 - 2013
    Lecturer, School of Business
  • 2009 - 2010
    Postdoctoral Researcher, Monash University
  • 2005 - 2009
    PhD Candidate, Monash University
  • 1999 - 2005
    Senior Engineer, ST Electronics Engineering
  • 1996 - 1999
    Project Engineer, ST Electronics Engineering
  • 1992 - 1996
    Engineer, Smith Corona/Compaq Asia

Refereed Journal Articles:

  • S.C. Tan & J. Tan (2018).Blind spots in Star Coordinate Visualization: Analysis and correction.Pattern Recognition Letters. 106. 7-12.
  • K.M. Ting, G.T. Zhou, L.T. Fei & S.C. Tan (2013). Mass estimation. Machine Learning Journal. 90(1), 127-160.
  • S.C. Tan, K.M. Ting & S.W. Teng (2011). A General Stochastic Clustering Method for Automatic Cluster Discovery. Pattern Recognition Journal. 44(10-11), 2786-2799.
  • K.M. Ting, J.R. Wells, S.C. Tan, S.W. Teng & G.I. Webb. (2011). Feature-Subspace Aggregating: Ensembles for Stable and Unstable Learners. Machine Learning Journal. 82(3), 375-397.
  • S.C., Tan. (2003) An Object Oriented Timetabling Framework. International Journal of Information Technology. Singapore Computer Society. 9 (1), 31-46.

Book Chapter:

  • S.C. Tan & P. Gupta (2023). Analytics in the Age of Disruption. In Leading in a Digitally Disruptive World. World Scientific. (Forthcoming)

Refereed Conference Papers:

  • S. C. Tan (2023). Enhancing Regression Tree Predictions with Terminal-Node Anomaly Detection. The 6th Artificial Intelligence and Cloud Computing Conference (AICCC 2023). ACM Conference Proceedings (ISBN: 979-8-4007-1622-5). Dec 2023.
  • S. C. Tan & S. Zhu (2023). Binary search of the optimal cut-point value in ROC analysis using the F1 score. International Conference on Engineering Mathematics and Physics (ICEMP 2023). IOP Science Conference Proceedings. July 2023.
  • D. Emmanuel, S. C. Tan & P. Gupta (2023). Analysing Online Review by Bank Employees: A Predictive Analytics Approach. The 25th International Conference on Information Integration and Web Intelligence (iiWAS2023). Springer Lecture Notes in Computer Science. (Dec 2023)
  • S. C. Tan(2018).Improving Association Rule Mining Using Clustering-based Discretization of Numerical Data. International Conference on Intelligent and Innovative Computing Applications (ICONIC 2018).
  • S.C. Tan, & J. Tan. (2017) Lost in translation: The fundamental flaws in star coordinate visualizations. International Conference on Computational Science (ICCS 2017).
  • S. C. Tan & S. Tong(2016).Fast retrievals of test-pad coordinates from photo images of printed circuit boards. International Conference on Advanced Mechatronic Systems (ICAMechS 2016).
  • S.C. Tan (2015) Using Supervised Attribute Selection for Unsupervised Learning. The Fourth International Conference on Advanced Computer Science Applications and Technologies (ASCAT 2015).
  • S.C. Tan, P.S. Lau & X.W. Yu (2015) Finding similar time series in sales transaction data. The International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems.
  • S.C. Tan & B. H. Sim (2014) A Pragmatic Approach to Summarize Association Rules in Business Analytics Projects. The International Conference on Technologies and Applications of Artificial Intelligence (TAAI 2014).
  • S.C. Tan, S.H. Yip & A. Rahman (2014) One Pass Outlier Detection for Streaming Categorical Data. The 3rd International Workshop on Intelligent Data Analysis and Management.
  • S.C. Tan (2014) Visualising Outliers in Nominal Data. The 8th International Conference on Knowledge

    Management in Organizations (KMO 2013).

  • S.C. Tan & P.S. Lau (2014) Time series clustering: A superior alternative for market basket analysis. The First International Conference on Advanced Data and Information Engineering (DaEng-2013).
  • S.C. Tan. (2012) Simplifying and improving swarm-based clustering. Congress on Evolutionary Computation (CEC 2012).
  • S.C. Tan, K.M. Ting & T.F. Liu. (2011) Fast Anomaly Detection for Streaming Data. International Joint Conference on Artificial Intelligence (IJCAI 2011).
  • S.C. Tan, K.M. Ting & S.W. Teng. (2011) Simplifying and Improving Ant-based Clustering. International Conference on Computational Science (ICCS 2011).
  • Shanghai Rural Commercial Bank – Consultant for Executive Training
  • SPSS Singapore - Associate Consultant
  • Danfoss Asia Pacific – Consultant for Executive Training
  • US Air Force Office of Scientific Research (AFOSR) – Researcher on Anomaly Detection
  • Monash University – Researcher on Classifier Ensemble
  • Business Analytics; Decision Tree; Anomaly Detection; Ensemble Learning; Clustering
  • Best Paper Award. The First International Conference on Advanced Data and Information Engineering (DaEng-2013).
  • Monash Postgraduate Publication Award – 2009
  • Best presentation award. Evolutionary Clustering (IEEE Congress on Evolutionary Computation) – 2006
  • Monash Graduate Scholarship - 2005
  • Monash International Postgraduate Scholarship - 2005
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