👋 Hi, I’m Xavier Lefebvre, a soon-to-be Ph.D. graduate with Data Science experience.
With a solid foundation in complex mathematical modeling, statistics, and machine learning, I bring unique blend of analytical rigor and problem-solving prowess, ready to drive impactful insights and innovations.
Let's explore the possibilities of AI together! 🚀
During my academic career I have led initiatives leveraging advanced statistical techniques and machine learning algorithms to drive strategic decision-making. My experience includes not just analysis, but also effectively communicating data-driven narratives to stakeholders across diverse domains. Furthermore, this work led to significant advancements in science and was published in reknowned peer-reviewed scientific journals. The link to these publications is provided in each repository.
The Machine Learning and Advanced Analytics section showcases the main projects I have worked on during my academic career, in the form of Jupyter notebooks. The Deep learning section presents data science tools that were used during my Ph.D. For this section, all the projects are within the same repository.
- Development of an algorithm that defines timeseries based on input parameters.
- Data-driven convergence analysis to define the best input parameters for the algorithm.
- Data analytics and statistical analysis of the aerosol generation source.
- Definition of a Linear Regression model for dimensional analysis.
- Random Forest Regression machine learning model that predicts the energy saved by a large building using the novel technology.
- Development of a Statistical quantitative risk analysis model for airborne disease transmission
- Data analytics and statistical analysis of the aerosol generation source.
- Definition of a Linear Regression model for dimensional analysis.
- Data cleaning, grouping of multiple datasets and handling large semi-structured datasets.
- Development of a Classification model that predicts the viability of the pathogens inside the aerosol.
- Data analytics and statistical analysis for the comparison of 4 datasets structured differently.
- Definition of a Linear Regression model for dimensional analysis.
- Development of two physics-based mathematical algorithms to correct previous models.
- Data analytics and statistical analysis of the aerosol generation source.
- Definition of a Linear Regression model for dimensional analysis.
- Development of three physics-based mathematical algorithms to explain new science observations.
- Deployment of two evaporation models with a variety of input parameters.