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This page is under massive construction. I am not Einstein.

I believe the technology we need to address the most pressing issues humanity faces cannot be designed without AI first helping us understand the natural world. My main interests lie in the design of AI for Science systems, and leveraging them to enable breakthroughs in bioengineering.

My path has been winding. I’m a multidisciplinary researcher, having first studied Psychology at Queen’s University, then Neuroscience at York University. I followed that up with applied biomarker development research in Psychiatry at CAMH before studying Machine Learning at Mila and the Université de Montréal. I did internships on ML applications in Radiology with Imagia and uncertainty estimation with Google. I worked on automated portfolio construction for CDPQ as part of my work with the Applied Machine Learning team at Mila, and worked on deep learning method for RNA biology with Deep Genomics, before landing my current contract Research Engineer position with Yoshua Bengio’s group at Mila, with a focus on open source tool development and applications of machine learning, particularly GFlowNets, in the area of biological discovery.

I consider myself a strong generalist who loves science and has a knack for building bridges between disciplines. For me, science is only a piece of the puzzle, and I’m fascinated by all of the steps required to build something useful.

Long term, I’m most interested in use of AI to power new scientific breakthroughs, and particularly to discover new technologies to fight climate change, improve food security, and to power continued growth of the economy without compromising the sustainability of our planet.

I’m also an amateur photographer and musician. I’ve peppered some of my photos throughout the site, and you can check out my Soundcloud for some rough demos.