Amir Mirzaeinia
Papers
2
Total Citations
7
H-Index
2
About
Amir Mirzaeinia is a researcher focused on advancing autonomous vehicle navigation, with a particular emphasis on real-time motion planning in dynamic, obstacle-rich environments. His work addresses one of the most pressing challenges in self-driving technology: ensuring safe and efficient trajectory planning when vehicles must contend with moving obstacles and unpredictable surroundings. His most-cited paper, "Real-Time Motion Planning for Autonomous Vehicles in Dynamic Environments" (2025), has already garnered 5 citations, reflecting growing interest in his contributions to this critical area of robotics and artificial intelligence. By developing algorithms that enable autonomous systems to make split-second decisions, Mirzaeinia’s research bridges the gap between theoretical planning and practical deployment. His work is particularly relevant for applications in urban mobility, logistics, and safety-critical autonomous systems. As the field accelerates toward fully autonomous transportation, Mirzaeinia’s innovations in real-time adaptability and collision avoidance stand out as foundational contributions, earning him recognition among peers and positioning him as a rising voice in the next generation of intelligent vehicle research.
Research Focus
Key Achievements
Top Papers
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