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Vanessa McNealis is a research fellow specializing in causal inference and complex observational data. She obtained her M.Sc. in Statistics from Université de Montréal in 2020 and is expected to complete her Ph.D. in Biostatistics at McGill University in 2024. Her research focuses on developing causal inference methods in settings with dependence, particularly within social network data. Vanessas' work addresses the challenges associated with causal inference in observational social network data, which often suffer from unmeasured network confounding, interference, and contagion. She is particularly interested in disentangling effects due to the influence of selection and the presence of homophily confounding, as well as performing causal inferences in dynamic networks. Her closely related research examines data obtained through respondent-driven sampling (RDS), employing chain-referral methods to sample hard-to-reach populations. Vanessa has contributed to various projects as a statistician in the fields of cardiometabolic health in pediatric populations and plant science.