Bryan Saldivar is a data scientist and machine learning researcher based in Barcelona with nine years of experience applying AI to bioinformatics, medical imaging, and production-scale computer vision. He holds a PhD focused on ML for omics data and has transitioned academic research into real-world systems鈥攆rom TB diagnosis models to personalized nutrition studies and current postdoctoral work at IRB Barcelona. At Cyberette he builds and deploys image/video manipulation detection models and manages large-scale datasets, combining research-grade rigor with production readiness. He also has a background in virtualization and technology intelligence, which helps him bridge infrastructure, reproducibility, and deployment gaps that often stall ML projects. Active online through publications, code, and videos, he blends deep domain knowledge with practical engineering to push ML systems from prototypes to scalable products.
9 years of coding experience
2 years of employment as a software developer
Scholar, Artificial Intelligence, Scholar, Artificial Intelligence at Pi School
Doctor of Philosophy - PhD, Machine learning applied on omics data, Doctor of Philosophy - PhD, Machine learning applied on omics data at Universitat Rovira i Virgili
Master's degree, Science,Technology and Innovation Policies and Management, Master's degree, Science,Technology and Innovation Policies and Management at Universidad Peruana Cayetano Heredia
Bachelor of Applied Science (B.A.Sc.), Telecommunications Engineering, Bachelor of Applied Science (B.A.Sc.), Telecommunications Engineering at Universidad Tecnol贸gica del Per煤
Korean, english - toefl: 103/120 (taken: 2017), Spanish
Tutorial to train a tensorflow CNN model with image batches from disk
Contributions:9 PRs, 76 pushes, 2 branches in 1 year 4 months
deep-learningdiskcnn-tensorflowbatchestensorflow
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