Postdoctoral Research Fellow at Paul G. Allen School of Computer Science & Engineering
Seattle, Washington, United States
Join Prog.AI to see contacts
Join Prog.AI to see contacts
Summary
👤
Senior
🎓
Top School
Jacob Sacks is a postdoctoral researcher at the Paul G. Allen School, University of Washington, specializing in how learning sculpts neural population activity for motor control and decision making. He combines task-optimized and data-driven recurrent neural networks with tools from deep learning, optimal control, reinforcement learning, and graphical models to probe rapid adaptation versus multi-day learning dynamics. His PhD work integrated learned components into model predictive control to boost controller performance and efficiency, bridging robotics and neuroscience. A NIH T32 Computational Neuroscience fellow with a decade of research experience, he brings a rare mix of theoretical rigor and applied systems thinking across disciplines from biomedical engineering to machine learning. Colleagues value his ability to translate control-theoretic insights into interpretable models of neural population reorganization.
10 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science and Engineering, Doctor of Philosophy - PhD Computer Science and Engineering at University of Washington
Bachelor’s Degree Biomedical Engineering, Bachelor’s Degree Biomedical Engineering at The University of Texas at Austin
Master of Science - MS Electrical and Computer Engineering, Master of Science - MS Electrical and Computer Engineering at Georgia Institute of Technology
Bioengineering, Bioengineering at University of Pittsburgh
Contributions:4 pushes, 1 branch in 1 year 5 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.
Request Free Trial
Jacob Sacks - Postdoctoral Research Fellow at Paul G. Allen School of Computer Science & Engineering