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黃禮珊 教授

姓名  Name：黃禮珊  Li-Shan Huang
職稱  Title  ：教授  Professor

研究領域 Research areas：曲線估計 curve estimation、生物統計 biostatistics
研究室 Office：綜合三館   807室   General Building III  Room 807

分機  Phone Extension：33183 
信箱 Email：lhuang@stat.nthu.edu.tw
 

學歷 Education

 

經歷 Experience

  • 國立清華大學統計學研究所教授，Professor, National Tsing Hua University，2011/02~
  • 國立清華大學統計學研究所所長，Director, Institute of Statistics, National Tsing Hua University，2012/08~2015/07
  • 國立清華大學統計學研究所客座副教授，Visiting Associate Professor, National Tsing Hua University，2009/08~2010/04
  • 美國羅徹斯特大學醫學中心生物統計系副教授，Associate Professor, Dept. of Biostatistics, University of Rochester，2004/07~2009/01, with tenure 2009/02~2013/01 (absence leave 2009/08-2010/04 and 2011/02-2013/01)
  • 美國羅徹斯特大學醫學中心生物統計系助理教授，Assistant Professor, Dept. of Biostatistics, University of Rochester
  • 美國羅徹斯特大學醫學中心生物統計系博士後研究 ，Research Postdoctoral Fellow, Dept. of Biostatistics, University of Rochester
  • 澳洲國立大學博士後研究，Research Postdoctoral Fellow, Australian National University
  • 美國佛羅里達州立大學統計系助理教授，Assistant Professor, Dept. of Statistics, Florida State University

 

研究領域 Research Areas

　　My research focuses on nonparametric curve estimation, to relax assumptions on the form of the regression or density function. This is a flexible and useful approach that allows the data to determine a curve for itself. A different research interest involves statistical applications in biomedical sciences. Real-world phenomena often bring up interesting statistical questions and challenges. I have collaborated with researchers in animal medicine, environmental health, obstetrics and gynecology, and cancer.

Awards:

§   American Statistical Association (ASA) Fellow 2021

§   傑出人才發展基金會99年度第二期積極爭取國外優秀年輕學者獎助

§   First-Year Assistant Professor Research Award, 1996, Florida State University

§   Graduate Teaching Award, 1992, Department of Statistics, University of North Carolina at Chapel Hill

§   Phi Tau Phi Scholastic Honor Society, 1990

PI-Grants:

§   TAIWAN NSTC grant科技部計劃 NSTC 111-2118-M-007-004-MY2

§   Taiwan MOST grant科技部計劃MOST 109-2118-M-007-001-MY2

§   Taiwan MOST grant科技部計劃MOST 107-2118-M-007-002-MY2

§   Taiwan MOST grant科技部計劃MOST 105-2118-M-007-006-MY2

§   Taiwan MOST grant科技部計劃MOST 103-2118-M-007-001-MY2

§   TAIWAN NSC grant國科會計劃NSC 101-2118-M-007-002-MY2

§   TAIWAN NSC grant國科會計劃NSC 100-2118-M-007-001

§   US NIH/NCI grant R21CA131603-01, 4/1/2008 --3/31/2012

§   US NSF Research Planning Grants for Women Scientists and Engineers DMS-9710084, 12/1/1997- 11/30/1998

研究成果　　

 　　Selected References:

  • Fan, J., Gijbels, I., Hu, T.-C. and Huang, L.-S. (1996). An asymptotic study of variable bandwidth selection for local polynomial regression. Statistica Sinica 6, 113-127.
  • Huang, L.-S. (1997). Testing goodness-of-fit based on a roughness measure. Journal of the American Statistical Association 92, 1399-1402.
  • Huang, L.-S. and Fan J. (1999). Nonparametric estimation of quadratic regression functionals. Bernoulli 5, 927-949.
  • Huang, L.-S. and Smith, R.L. (1999). Meteorological-dependent trends in urban ozone. Environmetrics 10, 103-118.
  • Fan, J. and Huang, L.-S. (1999). Rates of convergence for the pre-asymptotic substitution bandwidth selector. Statistics and Probability Letters 43, 309-316.
  • Huang, L.-S. (2001). Testing the adequacy of a linear model via critical smoothing. Journal of Statistical Computation and Simulation 68, 281-294.
  • Hall, P., Huang, L.-S., Gifford, J. and Gijbels, I. (2001). Nonparametric estimation of hazard rate under the constraint of monotonicity. Journal of Computational and Graphical Statistics 10, 592-614.
  • Hall, P. and Huang, L.-S. (2001). Nonparametric kernel regression subject to monotonicity constraints. Annals of Statistics 29, 624-647.
  • Fan, J. and Huang, L.-S. (2001). Goodness-of-fit tests for parametric regression models. Journal of the American Statistical Association 96, 640-652.
  • Huang, L.-S. (2001). A roughness-penalty view of kernel smoothing. Statistics and Probability Letters 52, 85-89.
  • Hall, P. and Huang, L.-S. (2002). Unimodal density estimation using kernel methods. Statistica Sinica 12, 965-990.
  • Myers, G.J., Davidson, P., Cox, C., Shamlaye, C., Palumbo, D., Cernuchiarti, E., Sloane-Reeves, J., Wilding, G. E., Kost, J., Huang, L.-S., and Clarkson, T. (2003). Prenatal methylmercury exposure from ocean fish consumption in the Seychelles child development study. Lancet 361, 1686-1692.
  • Huang, L.-S., Cox, C., Wilding, G.E., Myers, G.J., Davidson, P., Cernuchiarti, E., Sloane-Reeves, J., Shamlaye, C. and Clarkson, T. (2003). Using measurement error models to assess effects of prenatal and postnatal methylmercury exposure in the Seychelles child development study. Environmental Research 93, 115-122.
  • Huang, L.-S., Wang, H., and Cox, C. (2005). Assessing interaction effects in linear measurement error models. Journal of the Royal Statistical Society Series C Applied Statistics 1, 21-30.
  • Braun, W. J. and Huang, L.-S. (2005). Kernel spline regression. Canadian Journal of Statistics 33, 259-278.
  • Huang, L.-S., Cox, C., Myers, G.J., Davidson, P., Cernuchiarti, E., Sloane-Reeves, J., Shamlaye, C. and Clarkson, T. (2005). Exploring nonlinear association between prenatal methylmercury exposure from fish consumption and child development: Evaluation of the Seychelles Child Development Study nine-year data using semiparametric additive models. Environmental Research 97, 100-108.
  • Huang, L.-S., Myers, G.J., Davidson, P.W., Cox, C., Xiao, F., Thurston, S.W., Cernuchiarti, E., Shamlaye, C.F., Sloane-Reeves, J., Georger L. and Clarkson, T.W. (2007). Is susceptibility to prenatal methylmercury exposure from fish consumption non-homogeneous? Tree-structured analysis for the Seychelles child development study. NeuroToxicology, 28, 1237-1244.
  • Huang, L.-S. and Chen, J. (2008). Analysis of variance, coefficient of determination, and F-test for local polynomial regression. Annals of Statistics, 36, 2085-2109.
  • He, H. and Huang, L.-S. (2009). Double-smoothing for bias reduction in local linear regression. Journal of Statistical Planning and Inference, 139, 1056-1072.
  • Huang, L.-S. and Su, H. (2009). Nonparametric F-tests for nested global and local polynomial models. Journal of Statistical Planning and Inference, 139, 1372-1380.
  • Huang, L.-S. and Davidson, P.W. (2010). Analysis of Variance and F-Tests for Partial Linear Models with Applications to Environmental Health Data. Journal of the American Statistical Association, http://pubs.amstat.org/doi/pdf/10.1198/jasa.2010.ap08274
  • Lynch, M.L., Huang, L.-S., Cox, C., Davidson, P.W., Strain, J.J., Myers, G.J., Bonham, M.P., Shamlaye, C.F., Stokes-Riner, A., Wallace, J.M.W., Duffy, E.D. and Clarkson, T.W. (2011) Varying coefficient function models to explore interactions between maternal nutritional status and prenatal methylmercury toxicity in the Seychelles Child Development Nutrition Study. Environmental Research, 111, 75-80.
  • Huang, L.-S. and Chan, K.-S. (2014) Local polynomial and penalized trigonometric series regression. Statistica Sinica, 24, 1215-1238.
  • Hanin, L., and Huang, L.-S. (2014) Identifiability of cure models revisited. Journal of Multivariate Analysis, 130, 261-274.
  • Gao, H.-H. and Huang, L.-S. (2016) Sample size planning for testing significance of curves. Journal of Applied Statistics, 43, 2019-2028. http://dx.doi.org/10.1080/02664763.2015.1126238 
  • Härdle, W. K. and Huang*, L.-S. (2019) Analysis of deviance for hypothesis testing in generalized partially linear models. Journal of Business and Economic Statistics, 37, 322-333. http://dx.doi.org/10.1080/07350015.2017.1330693
  • Huang*, L.-S., Cory-Slechta, D.A., Cox, C., Thurston, S.W., Shamlaye, C.F., Watson, G.E., van Wijngaarden, E., Zareba, G., Strain, J.J., Myers, G.J.,  and Davidson, P.W. (2018) Analysis of nonlinear associations between prenatal methylmercury exposure from fish consumption and neurodevelopmental outcomes in the main cohort at 17 years from the Seychelles Child Development Study. Stochastic Environmental  Research and Risk Assessment 32(4), 893-904. https://doi.org/10.1007/s00477-017-1451-7
  • Lin*, L.-H. and Huang, L.-S. (2019) Connections between cure rates and survival probabilities in proportional hazards models. Stat, http://dx.doi.org/10.1002/sta4.255
  • Huang*, L.-S.  ,Li, L., Dunn, L., and He, M.(2021). Taking account of asymptomatic infections in modeling the transmission potential of the COVID-19 outbreak on the Diamond Princess cruise ship.  PLoS ONE 16(3): e0248273. https://doi.org/10.1371/journal.pone.0248273
  • Huang, W.-H., Huang*, L.-S. and Yang, C.-T. (2022) Invariant tests for functional data with application to an earthquake impact study.  Journal of Multivariate Analysis 189, 104894.  
    https://authors.elsevier.com/sd/article/S0047-259X(21)00172-X
  • Tripathi, Y. M., Chatla, S. B., Chang, Y. C. I., Huang*, L.-S., Shieh*, G. S. (2022) A nonlinear correlation measure with applications to gene expression data. PLoS ONE 17(6): e0270270. https://doi.org/10.1371/journal.pone.0270270
  • Wu, C.-Y., Huang*, L.-S. and Jin, Z. (2023) Decomposition and reproducing property of local polynomial equivalent kernels in varying coefficient models. Journal of Nonparametric Statistics DOI: 10.1080/10485252.2023.2217941.

 

See google scholar profile for full list of publications

 

Editorial Board

 

  • Deputy Editor for Contemporary Clinical Trials Communications, Sep 2020-present; Associate Editor for Contemporary Clinical Trials Communications, 2015 - August 2020
  • Associate Editor, Statistics in Biosciences, 2021 - present
  • Associate Editor, Communications in Statistics, 2021 - present

 

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