Summary
Mehrdad Zakershahrak is a Principal ML Scientist in Chicago with nine years of experience translating academic robotics research into large-scale industrial automation. He leads development and deployment of multi-modal robotic systems and a GPU-backed AWS model fleet that supports a 17M-SKU logistics operation, combining sensor fusion, motion planning, and multimodal learning to improve accuracy and efficiency. His PhD work in human–robot interaction and inverse reinforcement learning informs practical solutions for human-AI symbiosis, from telerobotic assembly to AMR coordination. Mehrdad has authored conference papers, holds patents in robotics, and mentors engineering teams while teaching as an adjunct professor. Known for tackling messy production data—performing ETL on billions of points and extracting 30+ automated insights—he bridges deep research with pragmatic, measurable impact.
9 years of coding experience
14 years of employment as a software developer
Bachelor of Engineering (B.Eng.), Computer Science, Bachelor of Engineering (B.Eng.), Computer Science at Shiraz University
Master of Science (M.Sc.), Information Technology, GPA 17.5 (out of 20), Master of Science (M.Sc.), Information Technology, GPA 17.5 (out of 20) at K. N. Toosi University of Technology
Doctor of Philosophy (PhD), Computer Science- Algorithmic Human Robot Interaction, Human-Machine Symbiosis, Doctor of Philosophy (PhD), Computer Science- Algorithmic Human Robot Interaction, Human-Machine Symbiosis at Arizona State University
Master of Science (M.S.), Computer Science, Master of Science (M.S.), Computer Science at University of Nebraska-Lincoln
English