Philip Schmidt, University of Waterloo
Research Assistant Professor
Waterloo, Ontario
pj2schmi@uwaterloo.ca
Office:
(519) 888-4567 ext. 36745
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Bio/Research
Philip J. Schmidt is a Research Assistant Professor in the Department of Civil and Environmental Engineering and a Statistician in the Water Science, Technology & Policy Group. He is accredited as an Associate Statistician by the Statistical Society of Canada.
Professor Schmidt’s resear...
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Professor Schmidt’s resear...
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Bio/Research
Philip J. Schmidt is a Research Assistant Professor in the Department of Civil and Environmental Engineering and a Statistician in the Water Science, Technology & Policy Group. He is accredited as an Associate Statistician by the Statistical Society of Canada.
Professor Schmidt’s research interests focus on quantitative microbial risk assessment (QMRA) applied in the context of drinking water treatment, dose-response modelling for enteric pathogens such as norovirus and Cryptosporidium, and statistical inference from various types of microbiological and water quality/treatment data. His interests span from fundamentals of statistical inference and modelling to drinking water and environmental microbiology, and ultimately to how this science informs policy that protects public health. His statistical expertise includes hierarchical probabilistic modelling, Bayesian analysis using Markov chain Monte Carlo, experimental design, and analysis of pitfalls in contemporary modelling practices (e.g., nonidentifiability, spurious models).
His previous experience includes a Visiting Fellowship at the Public Health Agency of Canada where he explored the implications of agricultural practices upon risks posed by waterborne pathogens in watersheds as well as private sector research and development work focused upon small-scale direct potable reuse (recycling domestic wastewater as a reliable supply of safe drinking water). He has experience applying failure mode and effects analysis (FMEA) to a complex automated water treatment system, reviewing ladder logic for this system, and analyzing continuously recorded data from numerous sensors to assess and understand system performance.
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Professor Schmidt’s research interests focus on quantitative microbial risk assessment (QMRA) applied in the context of drinking water treatment, dose-response modelling for enteric pathogens such as norovirus and Cryptosporidium, and statistical inference from various types of microbiological and water quality/treatment data. His interests span from fundamentals of statistical inference and modelling to drinking water and environmental microbiology, and ultimately to how this science informs policy that protects public health. His statistical expertise includes hierarchical probabilistic modelling, Bayesian analysis using Markov chain Monte Carlo, experimental design, and analysis of pitfalls in contemporary modelling practices (e.g., nonidentifiability, spurious models).
His previous experience includes a Visiting Fellowship at the Public Health Agency of Canada where he explored the implications of agricultural practices upon risks posed by waterborne pathogens in watersheds as well as private sector research and development work focused upon small-scale direct potable reuse (recycling domestic wastewater as a reliable supply of safe drinking water). He has experience applying failure mode and effects analysis (FMEA) to a complex automated water treatment system, reviewing ladder logic for this system, and analyzing continuously recorded data from numerous sensors to assess and understand system performance.
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