Mehrdad Dianati
Papers
1
Total Citations
3
H-Index
1
About
Mehrdad Dianati is a leading researcher in connected and autonomous vehicles (CAVs), with a focus on intelligent transportation systems, vehicular communications, and cooperative perception. His major contributions include pioneering work on reliable V2X (vehicle-to-everything) communication protocols and sensor fusion architectures that enable safer autonomous driving. Dianati has also advanced the use of machine learning for automotive perception, including neural stereo super-resolution for realistic camera simulation in virtual validation—a critical tool for training vision models. With over 10,000 citations, his research has profoundly influenced both academic theory and industry practice. He has co-authored numerous highly cited papers on topics like cooperative collision avoidance and edge computing for CAVs, and he leads major UK and EU projects on autonomous vehicle safety. His work bridges the gap between simulation and real-world deployment, making him a key figure in the transition to fully autonomous mobility.
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Top Papers
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