Mahdis Rabbani
Mentor at University of California, Davis
United States
Summary
👤
Senior🎓
Top SchoolMahdis Rabbani is a PhD candidate and mentor in Robotics and Control at UC Davis with eight years of experience developing interaction-aware decision-making and path-planning methods for autonomous and multi-agent systems. Her work weaves game theory, model predictive control, and data-driven modeling to enable agents that predict and respond to others in real time, and she has demonstrated this end-to-end—from fast Nash-seeking algorithms and Koopman-based identification to CARLA-integrated simulation and Julia-based nonlinear MPC prototypes. She leads the CORE Lab’s Vehicle Trajectory Prediction team, guiding students on deployable deep-learning pipelines and translating research into functional autonomous-driving components. Hands-on roots in sensor design, embedded control, and prototype instrumentation inform her practical approach to control and autonomy research. Notably, she pairs rigorous analytical skills with production-minded implementation, building both the math and the simulation/validation stacks that make interaction-aware autonomy work in realistic settings.
8 years of coding experience
Doctor of Philosophy - PhD Mechanical Engineering, Doctor of Philosophy - PhD Mechanical Engineering at University of California, DavisBachelor's degree Mechanical Engineering, Bachelor's degree Mechanical Engineering at University of TehranProgramming languages (1)
Github contributions (4)
amirmohammad1994/datadays2020
Mar 2020 - Mar 2020
Contributions:36 commits, 34 pushes in 8 days
mahdishb/MPI-ML
Mar 2024 - Aug 2024
Contributions:1 release, 7 pushes, 2 branches in 5 months
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