Prasanna Kolar
Papers
2
Total Citations
126
H-Index
2
About
Prasanna Kolar is a leading researcher in autonomous systems, with a primary focus on perception, sensor integration, and deep learning for smart mobility. His work is foundational to enabling safe, real-time decision-making in autonomous vehicles, robotics, and smart community infrastructure. Kolar’s most influential contribution is his comprehensive survey on data fusion techniques for laser and vision-based sensors, which has garnered 97 citations. This paper systematically addresses one of the most critical challenges in autonomous navigation: how to robustly combine heterogeneous sensor data for reliable perception. In a complementary vein, his work on pedestrian detection using deep Convolutional Neural Networks (29 citations) tackles the real-time safety imperative of recognizing pedestrians in dynamic environments—a key problem for autonomous driving, surveillance, and search-and-rescue operations. By advancing both the theoretical frameworks and practical implementations of sensor fusion and deep learning-based object detection, Kolar has helped shape the trajectory of modern autonomous systems research. His contributions are particularly notable for bridging the gap between algorithmic innovation and real-world deployment, making him a pivotal figure in the ongoing evolution of intelligent, autonomous mobility.
Research Focus
Key Achievements
Top Papers
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