Mohammad Dehghani Tezerjani
Papers
2
Total Citations
7
H-Index
2
About
Mohammad Dehghani Tezerjani is an emerging researcher whose work sits at the forefront of autonomous systems and intelligent transportation. His primary research focus centers on real-time motion planning for autonomous vehicles, tackling one of the most demanding challenges in self-driving technology: enabling vehicles to navigate safely and efficiently through dynamic environments populated with unpredictable moving obstacles. His investigations address the critical gap between theoretical trajectory planning algorithms and their practical, real-time implementation in complex, ever-changing scenarios — a problem that remains central to the commercial viability of autonomous driving systems. His most recognized contribution, "Real-Time Motion Planning for Autonomous Vehicles in Dynamic Environments," has already garnered citations across both its 2024 and 2025 iterations, accumulating a combined seven citations in a remarkably short publication window — a promising early indicator of the work's relevance to the autonomous systems community. The progression from his 2024 to 2025 publication suggests an active, iterative research agenda focused on refining and advancing solutions to trajectory planning under dynamic constraints. For students and researchers working in robotics, autonomous systems, or intelligent transportation, Dehghani Tezerjani's contributions represent a valuable and timely body of work worth following closely.
Research Focus
Key Achievements
Top Papers
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