PhD Student, Quantitative Life Sciences, Mila/McGill University
I study how structure emerges in learning systems, both biological and artificial. When we apply methods like dimensionality reduction or train neural networks on data, we're making implicit choices about what patterns matter. I'm interested in understanding how the shape of the data itself, its underlying geometry, guides these discoveries. I'm developing tools and frameworks for agentic AI systems that can reason geometrically about scientific data, learning to make principled analytical choices based on the intrinsic structure of the systems they're analyzing.
Organized and moderated weekly reading group exploring representation learning in biological systems. Open to researchers worldwide, covering foundational papers and emerging work in computational biology.
Designed bioinformatics workshop materials, directed qualified instructors, organized and supervised workshop delivery. Conducted code reviews for workshop materials. Coordinated fundraising efforts to support computational medicine initiatives.
Selected as Laboratory Representative (LabRep) to facilitate communication between students, postdocs, faculty, and staff. Organized assemblies, surveyed students on concerns, tracked proposals through to completion to enhance student involvement in decision-making.
Developing frameworks for geometrically intelligent agentic systems. Building tools for reasoning about manifold structure and guiding scientific discovery through geometric profiling and principled workflow selection.
Contributed to the development of Mila's official research template. Built the NLP module, remote launching with submitit/hydra, and code profiling infrastructure for seamless interaction with SLURM-managed cluster computing.
Ph.D. in Quantitative Life Sciences
McGill University, Montréal, Québec, Canada (Sept. 2023 – Present)
M.Sc. in Artificial Intelligence (Life Sciences Track)
Johannes Kepler Universität Linz, Upper Austria, Austria (Grad. 2024)
Exchange semester at Polytechnique Montréal, Québec, Canada (International Thematic Clusters in Engineering - Software)
M.Sc. in Computer Science
Ensenada Center for Scientific Research and Higher Education (CICESE), Baja California, México (Grad. 2020)
B.Sc. in Chemistry and Nanotechnology Engineering
Tec de Monterrey, Campus Monterrey, Nuevo León, México (Grad. 2016)
Current
Advisors
Thesis Committee