Summary
Jesus Montoya is a consultant and scientist with 11 years post-PhD experience specializing in computational methods for cryo-electron tomography applied to cellular and molecular problems in human disease. He has driven near-atomic structural studies of viral-antibody interactions and characterized organelle and aggregate morphologies in disease models, contributing to 19 peer-reviewed publications. Technically fluent in Python, scientific libraries, cryoET toolchains (EMAN2, IMOD, Relion5, AreTomo2) and ML approaches to correct imaging artifacts, he builds reproducible pipelines that improved motion correction, CTF estimation, and particle picking. Experienced in project and people management, he has mentored 20+ trainees, led interdisciplinary collaborations, and secured competitive fellowship support for high-impact structural projects. Based in San Francisco and currently expanding into data science through graduate studies at UT Austin, he blends deep domain expertise with growing data-science rigor. A practical innovator, he often generates simulated tomograms to validate ML annotations—a detail that highlights his habit of combining experimental realism with algorithmic solutions.
10 years of coding experience
17 years of employment as a software developer
PhD, Biomedical Sciences, PhD, Biomedical Sciences at Baylor College of Medicine
Bs., Physics, Bs., Physics at Universidad de Sonora
Master's degree, Data Science, Master's degree, Data Science at The University of Texas at Austin
Exchange Student, Physics/German/Biology, Exchange Student, Physics/German/Biology at The University of British Columbia
Associate's degree, Data Science, Associate's degree, Data Science at City College of San Francisco
English, Spanish, German, Portuguese, French, Japanese