Sleiman Safaoui is a PhD-trained robotics researcher and engineer with nine years of experience building risk-aware autonomy and deploying motion-planning and control algorithms on real multi-agent platforms. Currently an Associate at Exponent after research roles at UT Dallas and MERL, he specializes in sampling-, optimization-, and learning-based solutions that guarantee safety under prediction and process uncertainty. He developed tools like cvxRiskOpt, led hardware testbeds for RC cars and quadrotors, and translated novel MPC and RL ideas into physical experiments and publications. Comfortable collaborating across academia and industry, he also mentors students and manages lab hardware—bridging deep theory with hands-on system integration.
9 years of coding experience
5 years of employment as a software developer
Master's degree Electrical Engineering, Master's degree Electrical Engineering at The University of Texas at Dallas
Electrical and Computer Engineering, Electrical and Computer Engineering at American University of Beirut
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