Summary
Pablo Jadzinsky is a Senior Machine Learning Researcher with 11 years of experience bridging neuroscience and AI, currently based in Palo Alto and working on biologically inspired models at Cognitiv. His work focuses on how visual information is represented and computed in the retina, balancing energy efficiency and information encoding—a theme culminated in a recent submission to Neuron. Trained as a physicist (PhD, Stanford) with a long postdoc and academic teaching background, he combines rigorous experimental and theoretical approaches with practical ML engineering across startups and industry roles. Pablo prefers constraining architectures to match real neural circuits, pursuing CNN-based models whose units map onto real neurons, and has built production anomaly detection and computer vision systems in prior roles. He brings a rare mix of hands-on model building, neurophysiology insight, and applied data science across research and production environments.
11 years of coding experience
7 years of employment as a software developer
Licenciado Physics, Licenciado Physics at University of Buenos Aires
Ph.D. Applied Physics, Ph.D. Applied Physics at Stanford University
English, Spanish