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TIES-Wiley Best Student Presentation Award
The winners of the 2014 TIES-Wiley Best Student Presentation Award have been announced. This year’s prizes went to Yi Liu (University of Bath, UK) and Jussi Jousimo (University of Helsinki, Finland).
Yi Liu gave an oral presentation titled "Incorporating Large-scale Exposure Modelling into Studies of Air Pollution and Health", chosen for its demonstration of an innovative application of the large-scale Bayesian methodology to modelling air pollution and its impact on public health. Jussi Jousimo’s prize-winning talk "Inferring Habitat Use, Population Distribution and Total Population Size by Combining Individual-level and Population-level Data" developed a spatio-temporal Bayesian smoothing model for animal population assessment that combined multi-source information on individual- and population-levels.
First introduced in 1997 at the 8th Annual TIES Conference in Innsbruck, Austria, awards for the TIES-Wiley Best Student Presentation have since been given at each TIES conference. The presentations are given and judged during the conference and must represent work accomplished as a student The awards are co-sponsored by TIES and John Wiley & Sons, the publisher of the TIES official journal Environmetrics. The award consists of a certificate and a $500 cash prize.
Enjoy the latest Special Issues from Environmetrics
View the Special Issue now available online: Special Issue: Wildland Fires, a collection of papers that tackle some of the statistical issues concerned with characterizing wildfires and wildfire risk.
Featuring top papers:
Alisha Albert-Green, W. John Braun, David L. Martell and Douglas G. Woolford
Benjamin P. Bryant and Anthony L. Westerling
New! Environmetrics Discussion Papers
View the Research Article and Rejoinder papers by Adam A. Szpiro and Christopher J. Paciorek, published in Vol 24:8
Now read these top Discussion Papers based these original articles:
Measurement error in spatial exposure models: study design implicationsD.C. Thomas
Regression calibration in air pollution epidemiology with exposure estimated by spatio-temporal modeling,D. Spiegelman
Spatial exposure modeling: reconsidering the data-generating mechanism,C.A. Calder
We can understand complex models (at least, sometimes,J.S. Hodges
Measurement error in air pollution epidemiology: guidance for uncertain times,R. D. Peng