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.
PhD Electrical and Electronics Engineering from The University of Manchester.
- Postdoctoral Fellow - Robotics, Intelligent Systems & Control (RISC) Laboratory at King Abdullah University of Science and Technology KAUST, Robotics and AI Engineering Research. (Aug 2022 - Present)
- Postdoctoral Research Associates - Department of Electrical and Electronics Engineering the University of Manchester, Robotics and Artificial Intelligence for Nuclear Industry. (Aug 2021 - Aug 2022)
- R&D Electrical Engineer - king Abdulaziz city of science and technology KACST, Knowledge and Technology Transfer. (2016-2018)
- Abdullah S. Alharthi, Syed U. Yunas and K. B. Ozanyan, "Deep Learning for Monitoring of Human Gait: A Review," in IEEE Sensors Journal, vol. 19, no. 21, pp. 9575-9591, 1 Nov.1, 2019. DOI: 10.1109/JSEN.2019.2928777
- Abdullah S. Alharthi, Alexander J. Casson and Krikor B. Ozanyan,” Gait Spatiotemporal Signal Analysis for Parkinson’s Disease Detection and Severity Rating,” IEEE Sensors Journal, vol. 21, no. 2, pp. 1838 - 1848, 20 Aug 2020, DOI: 10.1109/JSEN.2020.3018262
- Abdullah S. Alharthi, Alexander J. Casson and Krikor B. Ozanyan, ”Spatiotemporal Analysis by Deep Learning of Gait Signatures from Floor Sensors,” IEEE Sensors Journal, vol. 21, no. 15, pp. 16904 – 16914, 2021. DOI: 10.1109/JSEN.2021.3078336
- Omar Costilla-Reyes, Ruben Vera-Rodriguez, Abdullah S Alharthi, Syed U Yunas, and Krikor B Ozanyan, “Deep learning in gait analysis for security and healthcare,” (accepted) Book Chapter in “Deep Learning: Algorithms and Applications”, Pedrycz W. and Chen S.-M., Eds. Springer Nature, vol. 865, pp. 299- 334, 2019. DOI: 10.1007/978-3-319-89629-8
- Abdullah S. Alharthi, Krikor B. Ozanyan, “Multimodal Gait Spatiotemporal Data of Different Walking Speeds Fusion,” IEEE Sensors conference, 2021. DOI: 10.1109/SENSORS47087.2021.9639816