Human-robot interaction

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

Abdulaziz Yaslam

M.S. Student, Electrical and Computer Engineering

sensors Human-robot interaction Rehabilitation

Education 2020.08 - Present M.S. Student in Bioengineering, King Abdullah University of Science and Technology, KSA 2016.07 - 2020.06 B.S. in Biomedical Engineering, University of California at Davis, USA Professional Profile 2021.05 - 2021.12 Master's Student Researcher, KAUST RISC Lab, KAUST, KSA 2016.09 - 2018.06 Teaching Assistant, Electrical Installations and Machines, UNAL, Colombia Honors and Awards 2018.07 "Best Poster" award in the North Carolina State University - KAUST Summer Internship Areas of Expertise and Research Interests Sensors Human-robot interaction Rehabilitation