I am a Postdoctoral Researcher in Pharmacology and Physiology at the Université de Montréal. My work bridges the gap between advanced experimental biology and computational data analysis, with a strong commitment to open science and reproducible research.

My Philosophy: It is important to me to combine effective data collection, based on careful planning, with the production of robust charts and conclusions through solid analytical pipelines.

My research specializes in neurovascular coupling, spanning from ex vivo (acute mouse brain slices) to in vivo models.

• Advanced Imaging & Electrophysiology: Extensive experience in contrast, confocal, and two-photon microscopy, combined with electrophysiological recordings.
• Tissue & Cellular Assays: Strong background in immunofluorescence (staining, acquisition, and quantification) as well as Flow Cytometry (FACS).
• Molecular Biology & Genomics: Proficient in genomic and protein workflows, including RNA extraction, RT-PCR, Western Blot, and bulk RNA-seq.

To extract meaningful insights from complex biomedical datasets, I develop custom, automated, and reproducible analytical pipelines:

• Data Analysis & Scripting: Writing efficient scripts in R and Python to ensure rapid, scalable, and reproducible data processing.
• Image Analysis: Automating image processing workflows using Fiji/ImageJ macro scripting.
• Rigorous Statistics: A core focus on applying just, robust, and accurate statistical models to physiological and genomic data.

• Image Processing: Fiji / ImageJ
• Programming Languages: Python, R
• Data Science & Stats: Pandas, NumPy, Scikit-Learn, ggplot2, Tidyverse
• Tools & Environment: VS Code, RStudio, Jupyter Notebooks, Git/GitHub

• Professional: LinkedIn
• Academic: ORCID iD | Google Scholar | Research Gate
• Location: Montréal, QC, Canada