Summary
Jeremy Binagia is an applied scientist at Amazon Robotics with eight years of experience building high-fidelity, physics-based simulators in C++ and Python to accelerate robotic manipulation research and deployment. He holds a Ph.D. from Stanford where he developed novel, massively parallel algorithms and produced the first fully resolved 3D simulations of microorganisms in viscoelastic fluids, demonstrating deep expertise in fluid-structure interaction and high-performance computing. At Amazon he focuses on modeling contact and pneumatics within Drake-based simulation engines, translating research-grade fidelity into production-capable performance. Jeremy combines rigorous computational science, hands-on systems optimization, and a track record of multidisciplinary collaboration across national labs and academia, making him adept at solving both theoretical and practical simulation challenges.
9 years of coding experience
3 years of employment as a software developer
Bachelor of Science (B.S.), Chemical Engineering, 4.0 GPA, Bachelor of Science (B.S.), Chemical Engineering, 4.0 GPA at The University of Texas at Austin
Doctor of Philosophy - PhD, Chemical Engineering, 4.068 GPA, Doctor of Philosophy - PhD, Chemical Engineering, 4.068 GPA at Stanford University
English