I received my Ph.D. in Statistics at the Dept. of Statistics, National Cheng Kung University, Taiwan, and started my expertise service in industrial statistics in 2018. I led and participated in at least 15 data science projects related to the manufacturing industry in ITRI, NCKU(postdoc), and Chimes AI. My research interest covers a) the theory and algorithmic generation of optimal experiment designs; and b) the surrogate modeling and acquisition strategies in Bayesian optimization.

Table of Contents

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Experience

Education

Publications

  1. M. Stehlik, P.-Y. Chen, W. K. Wong, J. Kiselak, “A Double Exponential Particle Swarm Optimization with non-uniform variates as stochastic tuning and guaranteed convergence to a global optimum with sample applications to finding optimal exact designs in biostatistics”, Applied Soft Computing Journal, vol. 163, 111913, 2024. (SCIE) [URL]
  2. P.-Y. Chen, R.-B. Chen, and W. K. Wong, “Particle swarm optimization for finding efficient longitudinal exact designs for nonlinear models”, The New England Journal of Statistics in Data Science, vol. 1, no. 3, pp. 299–313, 2023. [URL]
  3. P.-Y. Chen, R.-B. Chen, Y.-S. Chen, and W. K. Wong, “Numerical methods for finding A-optimal designs analytically”, Econometrics and Statistics, vol. 28, pp. 155–162, 2023. (ESCI) [URL]
  4. P.-Y. Chen, H.-M. Chang, Y.-T. Chen, J.-Y. Tzeng, and S.-M. Chang, “TensorTest2D: Fitting generalized linear models with matrix covariates.”, R Journal, vol. 14, no. 2, pp. 152–163, 2022. (SCIE) [URL]