I am Albara AH Ramli, a computer engineer and computer scientist. I received my B.Sc. in Computer Engineering from the Faculty of Engineering at the University of Tripoli, Libya, and my M.S. and Ph.D. in Computer Science from the College of Engineering at the University of California, Davis, USA, where I was advised by Professor Xin Liu and co-advised by Professor Erik Henricson. After my Ph.D., I spent three years as a Postdoctoral Scholar in the Neuromuscular Research Lab at UC Davis Health.
My research applies machine learning, both classical methods and deep learning, to IoT devices, human activity recognition and healthcare systems. My main contribution is Walk4Me, a system that turns wearable sensor data into digital outcome measures for children with Duchenne muscular dystrophy and for people with stroke or ALS.
My experience spans engineering and research: I have worked on IP/MPLS core networks and billing systems, and I founded a software company. I build the whole system myself: the sensor app, the model, and the server it runs on.
Research interests
Applied machine learning
Deep learning
Gait analysis
Human activity recognition
Wearable sensing
Digital health
Internet of Things
Network security
Polyglot programming
Education
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Ph.D.
Computer Science
College of Engineering, University of California, Davis, USA
Dissertation: Applied Machine Learning in Healthcare Systems: Classical and Deep Learning Approach for Gait Analysis and Activity Recognition (2023)
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M.S.
Computer Science
College of Engineering, University of California, Davis, USA
Thesis project: SBR Polyglot and Peer Platforms on IoT over Networks (2018)
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B.Sc.
Computer Engineering
Faculty of Engineering, University of Tripoli, Libya
Graduation project: Peer to Peer Connection Over Local Network System (P2P COLNS), supervised by Professor Shubat Senoussi Ahmeda (Owhida)