Manuel Razo-mejia
Scientist II, Computational Biology
Mountain View, California, United States
Summary
👤
Senior🎓
Top SchoolManuel Razo-mejia is a computational biologist and physical biologist with over a decade of experience applying biophysical modeling, Bayesian inference, and deep learning to decode and engineer biological systems. Currently a Scientist II in Computational Biology at Altos Labs after a postdoc at Stanford and a PhD in Biophysics from Caltech, he blends rigorous quantitative theory with hands-on computational methods to tackle complex biological data. He specializes in extracting mechanistic insight from noisy experiments, using probabilistic approaches and modern AI to push beyond standard statistical analyses. Based in Mountain View, he bridges academic depth and biotech impact, pairing a physics-rooted intuition with practical tool-building for real-world biological challenges. An underappreciated strength is his track record of translating theoretical models into computational pipelines that scale to high-throughput biological datasets.
10 years of coding experience
1 year of employment as a software developer
The National Polytechnic Institute of MexicoCalifornia Institute of Technology
Github Skills (76)
genetic10
circuit10
capacity10
bayesian-statistics9
probabilistic-graphical-models9
keybindings9
probabilistic-models9
bayesian9
julia8
bayesian-methods8
bayesian-inference8
adaptation8
mcmc8
probabilistic-programming8
probabilistic8
Programming languages (6)
Github contributions (5)
RPGroup-PBoC/rnaseq_barcode
Aug 2019 - Aug 2021
Contributions:82 pushes, 1 branch, 1 issue in 1 year 11 months
mrazomej/AutoEncoderToolkit.jl
May 2023 - Mar 2025
Julia package with several functions to train and analyze Autoencoder-based neural networks
Contributions:5 releases, 6 PRs, 218 pushes in 1 year 10 months
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