Summary
Esmaeil Seraj is a Staff Applied Scientist and Robotics AI tech lead with ~8 years of experience building production-grade robot learning systems for dexterous, contact-rich manipulation in manufacturing and logistics. He designs end-to-end robotics AI stacks that fuse perception, reasoning, and control—leveraging multimodal advances like vision-language models and vision-language-action policies to enable robust, real-world automation. His background spans academic research (PhD work on embodied team intelligence and multi-robot coordination) and industrial ML at Amazon, Ford, and GM, where he shipped systems for 3D reconstruction, affordance generation, planning, and learned policies integrated with optimization and reactive control. He has a strong foundation in computer vision, RL/LfD, and perception for safety-critical human–machine interaction, and has produced low-latency, high-accuracy models for gaze and in-cabin monitoring. Notably, he bridges rigorous research and engineering practice—turning algorithms into scalable, deployed systems—and has built interactive simulation tools and open-source toolboxes used in multi-agent and neural signal research. Based in Seattle, he blends deep academic rigor with hands-on delivery of complex robotic systems in industrial settings.
8 years of coding experience
10 years of employment as a software developer
Master’s Degree, Bioengineering and Biomedical Engineering, Master’s Degree, Bioengineering and Biomedical Engineering at Shiraz University
Doctor of Philosophy - PhD, Electrical and Computer Engineering, Doctor of Philosophy - PhD, Electrical and Computer Engineering at Georgia Institute of Technology
Bachelor’s Degree, Electrical and Electronics Engineering, Bachelor’s Degree, Electrical and Electronics Engineering at Tabriz University of Technology (Sahand)
English, Persian, French, Turkish