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Dr. TAN Matthias Hwai-yong (陳怀勇博士)

BEng(UTM), MEng(NUS), PhD(Georgia Tech)

Assistant Professor

Contact Information

Office: P6610 AC1
Phone: 3442????
Email: matthtan@cityu.edu.hk
Web: Google Scholar

Research Interests

  • Uncertainty Quantification in Computer Simulations
  • Design and Analysis of Physical and Computer Experiments
  • Robust Parameter Design
  • Engineering and Industrial Statistics
  • Statistical Learning

External Grants Obtained in the Capacity of PI
1. Early Career Scheme (ECS), Research Grants Council of Hong Kong: Stochastic Polynomial Interpolation for Uncertainty Quantification with Computer Experiments
2. General Research Fund (GRF), Project No 11226716, Research Grants Council of Hong Kong
3. General Research Fund (GRF), Project No 11201117, Research Grants Council of Hong Kong
4. General Research Fund (GRF), Project No 11205118, Research Grants Council of Hong Kong

For prospective students and post docs

I am looking for two post docs and Ph.D. students in the area of uncertainty quantification, statistical modeling, and design of experiments. If interested, please send me your CV by email. Please click on the link below for more information on my research, which contains illustrations from a collaborative computer experiments project led by me
(reported in paper 25):
https://drive.google.com/file/d/17-ebON7YdsW7pG6IKZgZ52NPP6AofIUd/view?usp=sharing

Peer Reviewed Journal Papers
1. Tan, M.H.Y. and Ng, S.H.* (2009). “Estimation of the Mean and Variance Response Surfaces when the Means and Variances of the Noise Variables are Unknown,” IIE Transactions, 41(11), 942-956.
http://www.tandfonline.com/doi/abs/10.1080/07408170902735418#.U-XfN_mSxqU
2. Tan, M.H.Y. and Wu, C.F.J.* (2012). “Generalized Selective Assembly,” IIE Transactions, 44(1), 27-42. (Feature Article: IE Magazine 2011, 43(10), page 50)
http://www.tandfonline.com/doi/abs/10.1080/0740817X.2010.551649#.U-Xfb_mSxqU
3. Tan, M.H.Y. and Wu, C.F.J.* (2012). “Robust Design Optimization with Quadratic Loss Derived From Gaussian Process Models,” Technometrics, 54(1), 51-63.
http://www.tandfonline.com/doi/abs/10.1080/00401706.2012.648866#.U-XfhPmSxqU
4. Tan, M.H.Y.* and Shi, J. (2012). “A Bayesian Approach for Interpreting Mean Shifts in Multivariate Quality Control,” Technometrics, 54(3), 294-307.
http://www.tandfonline.com/doi/abs/10.1080/00401706.2012.694789#.U-Xfm_mSxqU
5. Tan, M.H.Y. and Wu, C.F.J.* (2013). “A Bayesian Approach for Model Selection in Fractionated Split Plot Experiments with Applications in Robust Parameter Design,” Technometrics, 55(3), 359-372.
http://www.tandfonline.com/doi/abs/10.1080/00401706.2013.778790#.U-XgCvmSxqU
6. Tan, M.H.Y. (2013). “Minimax Designs for Finite Design Regions,” Technometrics, 55(3), 346-358.
http://www.tandfonline.com/doi/full/10.1080/00401706.2013.804439#.U-XgIfmSxqU
7. Sun,Y., Heo, Y., Tan, M.H.Y., Xie, H., Wu, C.F.J., and Augenbroe, G.* (2014). “Uncertainty Quantification of Microclimate Variables in Building Energy Models,” Journal of Building Performance Simulation, 7(1), 17-32.
http://www.tandfonline.com/doi/abs/10.1080/19401493.2012.757368#.U-Xf8vmSxqU
8. Tan, M.H.Y. (2014). “Bounded Loss Functions and the Characteristic Function Inversion Method for Computing Expected Loss,” Quality Technology and Quantitative Management, 11(4), 401-421.
http://www.tandfonline.com/doi/abs/10.1080/16843703.2014.11673353
9. Tan, M.H.Y. (2015). "Sequential Bayesian Polynomial Chaos Model Selection for Estimation of Sensitivity Indices," SIAM/ASA Journal on Uncertainty Quantification, 3(1), 146-168.
http://epubs.siam.org/doi/abs/10.1137/130931175
10. Tan, M.H.Y. (2015). "Stochastic Polynomial Interpolation for Uncertainty Quantification with Computer Experiments," Technometrics, 57(4), 457-467.
http://amstat.tandfonline.com/doi/full/10.1080/00401706.2014.950431
11. Tan, M.H.Y. (2015). "Robust Parameter Design with Computer Experiments Using Orthonormal Polynomials," Technometrics, 57(4), 468-478.
http://amstat.tandfonline.com/doi/full/10.1080/00401706.2014.969446#abstract
12. Simmons, B.*, Tan, M.H.Y., Wu, C.F.J, and Augenbroe, G. (2015). “Determining the Cost Optimum Among a Discrete Set of Building Technologies to Satisfy Stringent Energy Targets,” Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 29(4), 417-427.
http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=9994238&fileId=S0890060415000414
13. Tan, M.H.Y. and Zhang, Z.* (2016). “Wind Turbine Modeling with Data-driven Methods and Radially Uniform Designs,” IEEE Transactions on Industrial Informatics, 12(3), 1261-1269.
http://ieeexplore.ieee.org/abstract/document/7414473/
14. Tan, M.H.Y. (2016). “Monotonic Quantile Regression with Bernstein Polynomials for Stochastic Simulation,” Technometrics, 58(2), 180-190.
http://amstat.tandfonline.com/doi/abs/10.1080/00401706.2015.1027066#.VXoyPc-qqko
15. Han, M. and Tan, M.H.Y.* (2016). “Integrated Parameter and Tolerance Design with Computer Experiments”, IIE Transactions, 48(11), 1004-1015.
http://www.tandfonline.com/doi/abs/10.1080/0740817X.2016.1167289
16. Tan, M.H.Y. (2017). “Polynomial Metamodeling with Dimensional Analysis and the Effect Heredity Principle,” Quality Technology and Quantitative Management, 14(2), 195-213.
http://www.tandfonline.com/doi/full/10.1080/16843703.2016.1208491
17. Tan, M.H.Y. (2017). “Monotonic Metamodels for Deterministic Computer Experiments,” Technometrics, 59(1), 1-10.
http://www.tandfonline.com/doi/full/10.1080/00401706.2015.1105759
18. Han, M. and Tan, M.H.Y.* (2017). “Optimal Robust and Tolerance Design for Computer Experiments with Mixture Proportion Inputs”, Quality and Reliability Engineering International, 33(8), 2255-2267.
https://onlinelibrary.wiley.com/doi/10.1002/qre.2188
19. Tan, M.H.Y. (2018). "Gaussian Process Modeling of a Functional Output with Information from Boundary and Initial Conditions and Analytical Approximations", Technometrics, 60(2), 209-221.
https://www.tandfonline.com/doi/full/10.1080/00401706.2017.1345702
20. Tan, M.H.Y. (2018). “Gaussian Process Modeling with Boundary Information,” Statistica Sinica, 28(2), 621-648.
http://www3.stat.sinica.edu.tw/statistica/oldpdf/A28n24.pdf
21. Tan, M. H.Y.* and Li, G. (2018). "Gaussian Process Modeling Using the Principle of Superposition", Technometrics (just-accepted), 1-31.
https://amstat.tandfonline.com/doi/full/10.1080/00401706.2018.1473799
22. Li, G., Tan, M. H.Y.*, and Ng, S.H. (2018). "Metamodel-based Optimization of Stochastic Computer Models for Engineering Design under Uncertain Objective Function", IISE Transactions (just-accepted).
23. Tabatabaei, M.*, Lovison, A, Tan, M.H.Y., Hartikainen, M., and Miettinen, K. (2018). “ANOVA-MOP: Anova Decomposition for Multiobjective Optimization,” SIAM Journal on Optimization (just-accepted).
24. Li, G.*, Ng, S.H., and Tan, M.H.Y. (2018). “Bayesian Optimal Designs for Efficient Estimation of the Optimum Point with Generalised Linear Models,” Quality Technology and Quantitative Management (just-accepted).
25. Han, M., Liu, X., Huang, M., and Tan, M.H.Y.* (2018). “Integrated Parameter and Tolerance Optimization of a Centrifugal Compressor Based on a Complex Simulator,” Journal of Quality Technology (just-accepted).
26.

Peer Reviewed Conference Papers
1. Sun,Y., Heo, Y., Xie, H., Tan, M.H.Y., Wu, C.F.J., and Augenbroe, G. (2011). “Uncertainty Quantification of Microclimate Variables in Building Energy Simulation,” Proceedings of Building Simulation 2011: 12th Conference of the International Building Performance Simulation Association, Sydney, Australia, 2423-2430.
http://ibpsa.org/proceedings/BS2011/P_1758.pdf
2. Simmons, B., Tan, M.H.Y., Wu, C.F.J, Yu, Y., and Augenbroe, G. (2013). “Finding the Cost Optimal Mix of Building Energy Technologies that Satisfies a Set Operational Energy Reduction Target,” Proceedings of Building Simulation 2013: 13th Conference of the International Building Performance Simulation Association, Chambéry, France, 1852-1859.
http://www.ibpsa.org/proceedings/BS2013/p_1201.pdf

Others
1. Wu, C.F.J. and Tan, M.H.Y. (2013). “Youden Address: Quality Technology in the High-Tech Age,” ASQ Statistics Division Newsletter, 32(1), 13-17.

You are welcome to request any of my papers or Matlab code from me by email.

Invited Talks
• Symposium on Big Data Challenges for Predictive Modeling of Complex Systems, University of Hong Kong, Hong Kong, 2018.
https://cics.nd.edu/assets/300164/20181128_11_matthiashwaiyongtan.pdf

• Chinese Academy of Sciences Workshop on Uncertainty Quantification, Beijing, 2018.

• Technometrics Session, Joint Research Conference on Statistics in Quality, Industry, and Technology, Santa Fe, New Mexico, 2018.
Presentation Slides: Gaussian Process Modeling of a Functional Output with Information from Boundary and Initial Conditions and Analytical Approximations
https://drive.google.com/file/d/1VO-ccJrlqvzn0j3arCHvGavBjAi4uIil/view?usp=sharing

• Nanjing University of Aeronautics and Astronautics, 2018; Nanjing University of Science and Technology, 2018; Nankai University, 2017,
Presentation Slides: Uncertainty Quantification and Computer Experiments
https://drive.google.com/open?id=1nx4ed_0zPqo8pyKNVCos5e5VQKSmSRAo

• Workshop on Experimental Design and Uncertainty Quantification, National Cheng Kung University, Tainan, Taiwan, 2016.

• Quality Technology and Quantitative Management Session, INFORMS Annual Meeting, Nashville, 2016
Presentation Slides: Bounded Loss Functions and the Characteristic Function Inversion Method for Computing Expected Loss
https://drive.google.com/open?id=1-Wpgr1UEYLVZ6piDlmxox9kTCC7BBrfN

• Technometrics Session, Spring Research Conference on Statistics in Industry and Technology, Chicago, IL, 2016.
Presentation Slides: Monotonic Metamodels for Deterministic Computer Experiments
https://drive.google.com/file/d/1mkGLzg8stGAO0gfOiGVQrQo41gVDcX1P/view?usp=sharing

• 1st Sino-US Research Conference on Quality, Analytics, and Innovations, Shanghai, 2016.

• Designed Experiments: Recent Advances in Methods and Applications, Sydney, 2015.
Presentation Slides: Monotonic Quantile Regression with Bernstein Polynomials for Stochastic Simulation
https://drive.google.com/open?id=1ucPViyj_LITrgQTslM-XuZmd5gt5d9hz

• Technometrics Session, Spring Research Conference on Statistics in Industry and Technology, Cincinnati, Ohio, 2015.
Presentation Slides: Stochastic Polynomial Interpolation for Uncertainty Quantification with Computer Experiments
https://drive.google.com/file/d/0B61ItQFI-BxgaXdhdVlxUUN6SGs/view?usp=sharing

• Department of ISE, National University of Singapore, 2015.

• The International Congress on Industrial and Applied Mathematics (ICIAM), Beijing, 2015 (invited by organizer of mini-symposium on UQ).

• The Third International Conference on the Interface between Statistics and Engineering, City University of Hong Kong, 2014.

• International Statistical Institute Satellite Meeting on Statistics in Business, Industry and Risk Management, City University of Hong Kong, 2013.
Presentation Slides: Minimax Designs for Finite Design Regions
https://drive.google.com/open?id=15ztF53B1y-YLycLF9rSlhVG-ZsxhS1s7

PhD Students
1. Han Mei, September 2014 to July 2018. Currently: Assistant Professor at Nanjing University of Aeronautics and Astronautics
2. Jiang Fan, September 2016-
3. Ye Wenxing, September 2018-
4. Mohammad Pear Hossain (HKPFS recipient), September 2018-

Postdoctoral Researchers
1. Wang Yan (PhD from Chinese Academy of Sciences), Dec 2017 to June 2018. Currently: Assistant Professor at Beijing University of Technology
2. Zou Lu (PhD from Hong Kong University of Science and Technology), July 2018 to present

Visiting and Joint PhD Students
1. Mohammad Tabatabaei (University of Jyvaskyla), Nov 2015-Dec 2015, Mar 2016-June 2016.
2. Chong Sheng (Nankai University, Joint PhD), September 2018-
3. Li Zhaohui (Chinese Academy of Science, Joint PhD), September 2018-

Referee duties
Technometrics, Journal of the American Statistical Association, SIAM/ASA Journal on Uncertainty Quantification, Biometrika, Statistica Sinica, IIE Transactions, Journal of Quality Technology, Computational Statistics and Data Analysis, Journal of the Royal Statistical Society (Series C), Quality and Reliability Engineering International, Journal of the Operational Research Society, ASME Journal of Mechanical Design, The Asian Journal of Mathematics, Communications in Statistics - Theory and Methods, Proceedings of the 11th Workshop on Model-Oriented Data Analysis and Optimum Design mODa 11,


Last update date : 07 Dec 2018