GUOWEN HUANG

ABOUT ME

• Interest

  Environmental statistics; epidemiology; spatial statistics; Bayesian hierarchical modeling

  
  

• Research

  My research interests lie in the areas of environmental statistics and biostatistics, mainly focusing on developing novel air pollution models to estimate exposure and novel disease models to investigate their adverse impacts on our health.

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• Current research

  Currently, I am a postdoctoral fellow at the department of statistical sciences, University of Toronto, where I have been involved in three research projects.

  
  

  The first one is a project focusing on daily mortality and air quality supported by Health Canada. A novel multivariate time series model within Bayesian framework was proposed for exposure assessment. The main novelty contributed to literature is that seasonally varying covariances among pollutants are allowed, and the pollution model was implemented in stan with parallel subthreads to speed up computation. Then a case-crossover design and conditional logistic regression disease model is used to relate exposure to disease data, which allows exposure uncertainty to be propagated into disease model by making multiple sets of estimated exposure and then fit the disease model separately for each set before combining the estimated health effects.

  
  

  The second project is a prospective proportional mortality study to provide the first-ever direct national estimates of chronic respiratory disease, heart attack and stroke mortality from exposure to PM2.5 in India from 2001-2013.

  
  

  The third project is to investigate how the snake bite patterns change across space and interacted by time in India. The motivating study of this project is the mortality data from the India’s Million Death Study (MDS) conducted in 2001-2013, in which India is separated into 1 million small areas of about 150– 300 households based on the 10-year census, then all births and deaths in about 8,000 of these small areas were monitored. This is a joint project with Prof. Marta Blangiardo from Imperial College London, which is partially funded by the Mitacs Globalink Research Award.

RESEARCH

Paper

1. Guowen Huang; Patrick Brown; Hwashin H. Shin. Daily mortality/morbidity and air quality: using multivariate time series with seasonally-varying covariances. Journal of the American Statistical Association. In preparation.

2. Patrick Brown; Yurie Izawa Maher; Kalpana Balakrishnan; Sze Hang Fu; Rajesh Kumar; Joy Chakma; Geetha Menon; Rajesh Dikshit; RS Dhaliwal; Peter S Rodriguez; Guowen Huang; Rehana Begum; Howard Hu; George DSouza; Randeep Guleria. Mortality from Particulate Matter (PM2.5) in India: National Prospective Proportional Mortality Study. The Lancet Planetary Health. Submitted.

3. Hsin-Cheng Huang and Noel Cressie and Andrew Zammit-Mangion and Guowen Huang. False Discovery Rates to Detect Signals from Incomplete Spatially Aggregated Data. Journal of Computational and Graphical Statistics. Revised. （pdf）

4. Huang G, Chen L-J, Hwang W-H, Tzeng S, Huang H-C. Real-time PM2.5 mapping and anomaly detection from AirBoxes in Taiwan. Environmetrics. 2018;1-15. （pdf）

5. Huang G., Lee D. and Scott M. Multivariate space-time modelling of multiple air pollutants and their health effects accounting for exposure uncertainty, Statistics in Medicine. 2017; 37: 1134-1148. （pdf）

6. Huang G., Lee D. and Scott M. An integrated Bayesian model for estimating the long-term health effects of air pollution by fusing modelled and measured pollution data: A case study of nitrogen dioxide concentrations in Scotland, Spatial and Spatio-temporal Epidemiology. 2015;14-15: 63-74. （pdf）

7. Li H., Huang G., Qi E. Dynamic Facility Layout Problem Systems Based on Hybrid Ant Colony Optimization Algorithm, Journal of Industrial Engineering and Engineering Management. 2014;28(1): 110-118. (pdf)

8. Huang G., Liu H. Measuring Satisfaction of Two Level Employees in a Representative Chinese Steel Plant: A Structure Equation Modeling Approach. In: Qi E., Shen J., Dou R. (eds) The 19th International Conference on Industrial Engineering and Engineering Management. Springer, Berlin, Heidelberg. 2013;22: 231-238. (pdf)