A simple icon, consisting of a series of links surrounded by a circle, is a common symbol for a connection or hyperlink. The lines of the icon are outlined in a dark black color on the background, with the addition of military elements of the Saudi national identity such as the Ghutra, Shamaa, and Saudi Bisht, to reflect the distinctive local character of Qassim University.

Links to official Saudi educational websites end with

edu.sa

All links to official educational websites of government agencies in Saudi Arabia end with .edu.sa.

Black leather minimalist gesture tag, black circular grip, topped with a clear depiction of a Saudi tunic with a shamma and aqal, emphasizing the features of the Saudi bisht. This design symbolizes the concept of security and digital data privacy and reflects the identity of Qassim University.
protocol for encryption and security. HTTPS for encryption and security.
Secure websites in the Kingdom of Saudi Arabia use the HTTPS protocol for encryption.
Digital Government Authority

Faculty members

Content

Inside a building, a man dressed in a traditional white uniform with a red and white Saudi shemagh wears a neutral expression as if he were taking a picture of a faculty file at Qassim University.
Photo of the faculty member

basim abdullah sulaiman alhumaily

Lecturer
College of Engineering
section

Personal data

    Scientific qualifications

      Research interests

        Published research

        • Radar signal processing and its impact on deep learning-driven human activity recognition (2025-01-01)
        • Integrating millimeter-wave FMCW radar for investigating multi-height vital sign monitoring (2024-01-01)
        • VMD integrated FMCW radar system for non-invasive pediatric vital sign estimation (2023-01-01)
        • Real-Time Lightweight Deep Learning Models for Human Activity Recognition Using FMCW Radar (2024-01-01)
        • Non-Invasive Driver Activity Recognition using mmWave Radar (2026-01-01)
        • Benchmarking radar preprocessing techniques and transfer learning models for FMCW-based human activity recognition (2026-01-01)
        • Leveraging AI and radar for non-invasive fine-grained human activity monitoring (2026-01-01)
        • Multimodal Fusion of Heart Rate and Gaze Data For Real-Time Driver Monitoring in Naturalistic Driving (2025-01-01)
        • Evaluating Radar Signal Preprocessing Techniques for Improved Transfer Learning in Human Activity Recognition (2024-01-01)

        Teaching materials

          Cookies

          This website uses special cookies to ensure ease of use, improve your browsing experience, and clarify the terms and policies related to About user privacy. By continuing to browse this website, you acknowledge that you accept the use of cookies and the terms of the Privacy Policy