Summary
Savva Morozov is an applied scientist and PhD student in robotics at MIT CSAIL focused on building autonomous systems that quantify and act under uncertainty. With five years of experience across academic labs and industry, he has developed motion planning, trajectory optimization, and multi-arm coordination algorithms for legged robots, drones, and warehouse manipulators. At Amazon Robotics he now applies those skills to real-world warehouse arm planning and previously delivered multi-arm scheduling during his co-op. His research spans belief-space planning, hybrid-dynamics trajectory design for jumping and walking robots, and data-driven sensor models—work that bridges theoretical estimation with robust, tested pipelines on hardware. Comfortable moving between Kalman/particle-filter hybrids and model predictive control, he emphasizes run-time adaptation to improve speed and reduce control effort. Based in Cambridge, MA, Savva combines hands-on systems integration with formal approaches to uncertainty, aiming to make autonomy reliable outside the lab.
5 years of coding experience
3 years of employment as a software developer
Master of Science - MS, Electrical Engineering and Computer Science (Robotics), Master of Science - MS, Electrical Engineering and Computer Science (Robotics) at Massachusetts Institute of Technology
Bachelor of Science in Electrical Engineering, Bachelor of Science in Electrical Engineering at Rice University
Russian, English