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Dr. GAO Siyang (高思陽博士)

BS(PKU), PhD(Univ of Wisconsin)

Associate Professor

Contact Information

Office:  AC1-P6611
Phone: 34424759
Email: siyangao@cityu.edu.hk
Web: personal webpage

Research Interests

  • Simulation modeling and optimization
  • Applied probability
  • Discrete event dynamic systems
  • Healthcare management
Dr. Siyang Gao received a B.S. in Statistics and Probability from School of Mathematics at Peking University in 2009 and a Ph.D. in Industrial Engineering at University of Wisconsin-Madison in 2014. His research interests include simulation modeling and optimization, applied probability, discrete event dynamic systems, and healthcare management.


Publications Show All Publications Show Prominent Publications


Journal

  • Gao, S. , Shi, L. & Zhang, Z. (2018). A peak-over-threshold search method for global optimization. Automatica. 89. 83 - 91.
  • Xiao, H. & Gao, S. (2018). Simulation budget allocation for selecting the top-m designs with input uncertainty. IEEE Transactions on Automatic Control. 63(9). 3127 - 3134.
  • Gao, S. , Chen, W. & Shi, L. (2017). A new budget allocation framework for the expected opportunity cost. Operations Research. 65. 787 - 803.
  • Gao, S. & Chen, W. (2017). A partition-based random search for stochastic constrained optimization via simulation. IEEE Transactions on Automatic Control. 62. 740 - 752.
  • Gao, S. & Chen, W. (2017). Efficient feasibility determination with multiple performance measure constraints. IEEE Transactions on Automatic Control. 62. 113 - 122.
  • Gao, S. , Xiao, H. , Zhou, E. & Chen, W. (2017). Robust ranking and selection with optimal computing budget allocation. Automatica. 81. 30 - 36.
  • Xiao, H. & Gao, S. (2017). Simulation budget allocation for simultaneously selecting the best and worst subsets. Automatica. 84. 117 - 127.
  • Gao, S. & Chen, W. (2016). A new budget allocation framework for selecting top simulated designs. IIE Transactions. 48. 855 - 863.
  • Gao, S. & Chen, W. (2015). Efficient subset selection for the expected opportunity cost. Automatica. 59. 19 - 26.
  • Gao, S. & Shi, L. (2015). Selecting the best simulated design with the expected opportunity cost bound. IEEE Transactions on Automatic Control. 60(10). 2785 - 2790.


For prospective students

  • I am looking for qualified Ph.D. students (with strong background in mathematics, probability and statistics) to do research on simulation optimization and analysis. If you are interested, please send your CV and transcript to my email (siyangao@cityu.edu.hk) for consideration.


Links



Last update date : 19 Aug 2020