Associate Professor and Programme Director, Statistics
Office: T3-602-R18

Academic & Professional Qualifications
  • 1996-2000 College of Mathematics, Sichuan University, Bachelor of Science
  • 2000-2002 College of Mathematics, Graduate School of Sichuan University
  • 2002-2005 Department of Mathematics, Hong Kong Baptist University
Research Areas
  • Data Mining
  • Statistical Simulation
Selected Publications
  1. J.J. Jiang, P. He, K.T. Fang, An Interesting Property of The Arcsine Distribution and Its Applications, Statistics and Probability Letters, (2015), 105, 88-95
  2. P. He, M. Zhou, K.T. Fang, Principle points: Application to simulation of asymmetric mixture distribution. the 24th International Workshop on Matrices and Statistics, (2015), Haikou, China, P.R.
  3. X.P. Cheng, H, P. He, R.T. Tian, Combination of effective machine learning techniques and Chemometric analysis for evaluation of Bupleuri Radix through high-performance thin-layer chromatography, Anal. Methods, (2013), 5, 325-330. 
  4. P. He, Z.M. Zhang, Y.L. Zeng, Automated Baseline Correction with Adaptive Iteratively Roughness Penalty Spline Smoothing. Proceedings of the 9th International Chinese Statistical Association (ICSA) Conference, (2013), HKBU, China, P.R.
  5. Steven S. W., W. Li and P. He (2007) what makes institutional and individual investor trade excessively: evidence from China, Proceedings of the 15th annual Conference on Pacific Basin Finance, Economics, Accounting and Management, Vietnam.
  6. P. He, Kai-Tai Fang, Yi-Zeng Liang and Bo-Yan Li, (2005) A Generalized Boosting Algorithm and Its Application to Two-Class chemical Classification Problem, Analytica Chimica Acta . 543,181-191.
  7. P. He, C.J. Xu, Y.Z. Liang and K.T. Fang, (2004) Improving the Classification Accuracy in Chemistry Via Boosting Technique, Chemometrics and Intelligent Laboratory Systems . 70,39-46.
  8. P. He, K.T. Fang, Y.Z. Liang and C.J. Xu, (2003) The Decision Tree Combined with SIR and Its Applications to Classification of Mass Spectra, Journal of Data Science, 1, 425-445.
  9. K. Varmuza, P. He and K.T. Fang, (2003) Boosting Applied to Classification of Mass Spectral Data, Journal of Data Science, 1, 391-404
Courses Taught at UIC
  • Statistics for Business
  • Statistics for Science
  • Computer-Aided Data Analysis
  • Loss Models
  • Data Mining
  • Life Contingencies
  • Mathematics for Business
  • Mathematics for Science
  • Computational Finance
  • Actuarial Mathematics
  • Simulation