Teaching
My teaching philosophy is grounded in the principle that students learn computational and quantitative methods by doing, not by watching. I build courses and workshops around real data, real code, and real problems. Students leave with skills they can use immediately.
I design learning environments that are collaborative and accessible. In my lab, trainees at every level contribute to experiment design, grant-writing, and publications. I treat training as part of the research process, not separate from it.
Teaching Experience
2025 Université de Montréal fNIRS Theory and Preprocessing
2025 Université de Montréal EEG Data Preprocessing
2020/2021 University of Ottawa Neural Signal Processing
2017/2018 University of Ottawa Statistics
Mentorship and Equity
Training the next generation of scientists is not separate from my research program, but part of it. I am committed to building inclusive lab environments where trainees from underrepresented and neurodiverse groups are actively recruited and supported.
This commitment is reflected in my role as a CanNRT Postdoctoral Mentor and in the graduate mentorship program I founded at CHU Sainte-Justine. My research on sex differences in Neurodevelopmental disorders is itself equity-driven, addressing the diagnostic gaps that have historically disadvantaged women and girls. I bring that same lens to how I teach, recruit, and mentor.
Trainee Supervision
I have supervised 20+ trainees across PhD, MSc, and undergraduate levels at institutions including Université de Montréal, McGill University, Queen's University, University of Ottawa, and Carleton University. I involve trainees in the full research cycle, from study design through publication.
