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Research
I am interested in general applications of statistics in epidemiology. These past few years I have specialized in causal inference, the study of causality relationships between specific exposure and response variables. An example of the type of application on which I am currently working is the determination of the effects of inhaled corticosteroids used in the treatment of asthma on pregnant women and their babies.
My research themes in causal inference are:
- Mediation
- Model selection
- Graphical approaches
- Generalized propensity scores
- Modelling and miscellaneous applications
I have used the Bayesian paradigm for most of my previous work. I have notably worked on path sampling, an advanced integration technique that aims to estimate the marginal likelihood, an essential quantity for model selection in this context. Through this research I have developed an expertise in Markov Chain Monte Carlo (MCMC) techniques and in Bayesian modelling more generally
My list of publications is here.
Nouvelles
Nouvelles
- Nouvelle version du package R ExactMed
- Ismaïla interviewé par Actualités UQAM !
- Supers journées de recherche sur l'analyse de médiation organisées par
Milica Miočević et moi-même (Mediation Research Days 2021)
- Suivez les activités du centre de recherche facultaire en statistique et sciences des données STATQAM !
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Students
I am recruiting qualified and motivated MSc/PhD students (towards a degree in mathematics concentration statistics at UQAM) or post-doctoral fellows. Potential trainees should have a good background in statistics, very good computer skills and interest in data analysis in epidemiology.