Biographie
Versatile professional driven by solving complex problems using machine learning tools. A civil engineer by training (2004), holder of a master’s degree in water resources (2008) with a thesis on integrating Indigenous knowledge into machine learning-based expert systems for precipitation forecasting. PhD in water resources obtained in 2013, with a dissertation dedicated to the Mixture of Experts approach for probabilistic flood forecasting.
A postdoctoral internship completed in 2015 at CEHQ and Environment Canada enabled the optimization, using artificial intelligence, of the coupling between atmospheric, hydrological, and soil models.
In 2016, the entrepreneurial direction materialized with the development of early flood warning systems based on probabilistic approaches in artificial intelligence.
Since 2019, the founding of AppOX has paved the way for various projects, primarily in the field of healthcare administration in Quebec, with particular attention to interpretability and privacy protection:
– Assessment of non-compliance risk in medical billing without associated clinical activity.
– Automated acceptance of medical requests for the exceptional drug program.
– Detection of potentially inappropriate access to clinical registries.
– Use of large language models (LLMs) to interpret and classify client comments.
– Automation of the implementation of re-identification risk models in databases.
– Generation of synthetic data to strengthen the protection of confidential information, facilitate secure sharing, process imbalanced data, and support development in classical analytical environments.
