Sensor Fusion

Abdelgabar Ahmed

M.S. Student, King Abdullah University of Science and Technology

Indoor localization Autonomous Navigation Sensor Fusion

Working on robust urban localization by fusing GNSS, vision, and inertial sensors to mitigate multipath effects. Developing theoretical performance bounds on GNSS localizability using spatial statistical models of satellite geometry and signal availability.

Abdullah Alharthi

Postdoctoral Research Fellow, Electrical and Computer Engineering

data analysis Pattern Recognition Sensor Fusion Deep learning Human Gait Analysis Applications convolutional neural network Perception Human-robot interaction

Dr. Abdullah Alharthi's research centers around pattern recognition as a means to tackle a diverse array of new challenges, including how to learn intelligent behavior in complex, dynamic environments. His areas of expertise include cognition, perception, theory of mind, gait, and human-robot interaction. His work delves into both human kinetics and the comprehension and resolution of how humans and robots interact with one another in a dynamic setting. Dr. Alharthi employs Deep Learning techniques to tackle problems related to image, object, and signal recognition and classification