I'm a researcher focusing on deep learning applications in population genetics and precision health, working with Prof. Alexander Ioannidis at Stanford University's Department of Biomedical Data Science and UC Santa Cruz Genomics Institute.
Previously, I also collaborated with ML4SCI on quantum machine learning for high-energy physics with Prof. Sergei Gleyzer, and worked with Prof. Jordi Cortadella at UPC on developing a framework for automated chip floorplanning.
I completed my Bachelor's in Data Science and Engineering at the Polytechnic University of Catalonia (UPC), graduating as valedictorian and participating in exchanges at ETH Zurich and Stanford University.
Publications
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snputils: A Python Library for Processing Diverse Genomes
D. Bonet*, M. Comajoan Cara*, ..., A. Ioannidis
Poster presented at the American Society of Human Genetics (ASHG) Annual Meeting, 2024, Denver, Colorado, USA. Poster; GitHub. -
PopGenAdapt: Semi-Supervised Domain Adaptation for Genotype-to-Phenotype Prediction in Underrepresented Populations
M. Comajoan Cara, D. Mas Montserrat, A. Ioannidis
Oral presentation at the Pacific Symposium on Biocomputing (PSB), 2024, Puako, Hawaii, USA. Paper; bioRxiv; GitHub. -
Quantum Vision Transformers for Quark-Gluon Classification
M. Comajoan Cara, ..., S. Gleyzer
Published in Axioms, 2024; 13(5):323. Paper; arXiv; GitHub. -
$\mathbb{Z}_2 \times \mathbb{Z}_2$ Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks
Z. Dong, M. Comajoan Cara, ..., S. Gleyzer
Published in Axioms, 2024; 13(3):188. Paper; arXiv. -
Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics
E. Unlu, M. Comajoan Cara, ..., S. Gleyzer
Published in Axioms, 2024; 13(3):187. Paper; arXiv. -
A Comparison Between Invariant and Equivariant Classical and Quantum Graph Neural Networks
R. Forestano, M. Comajoan Cara, ..., S. Gleyzer
Published in Axioms, 2024; 13(3):160. Paper; arXiv.
We can only see a short distance ahead, but we can see plenty there that needs to be done.