Science as a
way of seeing.
I’m a neuroscientist turned AI engineer, drawn to the space between complex research questions and practical systems that help people.
COMING SOON
From understanding systems to building them.
My training began in neuroscience. I earned a PhD at McGill University and the Montreal Neurological Institute, then continued as a postdoctoral researcher at Mila and McGill University.
That work taught me how to reason through uncertainty, analyze complex neuroimaging data, and communicate findings across disciplines. It also made me deeply interested in the tools we use to turn information into insight.
Today, I bring that research mindset to applied AI. I build applications, agentic workflows, automation systems, and data-driven tools—always with an eye on the people and decisions they support.
As an independent consultant, I’m interested in collaborating on problems where careful analysis and pragmatic engineering can make a real difference.
A few things I bring
to the table.
Scientific rigor
Frame the right question, examine the evidence, and stay willing to revise the answer.
Technical depth
Move comfortably between data analysis, machine learning, application design, and implementation.
Practical focus
Build for real workflows and meaningful decisions, with clarity at every step.