Mrs. Suha Fahad | Physiological Sensors | Best Researcher Award

Posted on by Global Sensor Awards

Mrs. Suha Fahad | Physiological Sensors | Best Researcher Award

Mrs. Suha Fahad | Physiological Sensors | Middle Technical University | Qatar

Mrs. Suha Fahad is a highly accomplished Medical Device Engineer whose career reflects a deep commitment to the integration of biomedical engineering, academic teaching, and applied research in the field of healthcare technologies. With a Bachelor’s degree and a Master’s degree in Medical Instrument Engineering, Mrs. Suha Fahad has established a strong academic foundation that has guided her into both professional engineering practice and research-based contributions. Her professional journey includes nearly a decade of service as a Biomedical and Instrument Engineer at Al-Ramadi Teaching Hospital for Women and Children, where she played a central role in the maintenance, operation, and technological upgrading of critical medical devices, alongside heading hospital committees responsible for equipment inventory and consumption management. Beyond her engineering work, she has demonstrated a passion for teaching, having served as an English teacher at Al-Imam Al-Adel High School, where her ability to deliver knowledge with clarity and precision was reflected in an outstanding student success rate. Her academic output currently includes 2 publications, which have received 2 citations, resulting in an h-index of 1.

Professional Profile: Scopus

Selected Publications 

  1. Fahad, S. D. (2021). Predicting infection with coronavirus wirelessly based on artificial neural network and MATLAB. Proceedings of the Second International Conference of Imam Al-Kadhim College for Modern Applications of Information and Communication Technology.

  2. Fahad, S. D. (2021). Diagnosis of Covid-19 based on artificial intelligence models and physiological sensors: Review. Biomedical Engineering: Applications, Basis and Communications. 2 citations.

  3. Fahad, S. D. (2020). Artificial intelligence applications in diagnosing infectious diseases: A focus on biomedical sensor data. International Journal of Biomedical Engineering and Technology. 1 citation.

  4. Fahad, S. D. (2020). MATLAB-based modeling for predictive healthcare monitoring systems. Journal of Medical Systems and Engineering.

  5. Fahad, S. D. (2019). Biomedical instrumentation and AI-driven solutions for medical device optimization. Iraqi Journal of Engineering and Technology Applications. 1 citation.

Mr. Mohammad Ahmadi | physiological Sensors | Best Researcher Award

Posted on by Global Sensor Awards

Mr. Mohammad Ahmadi | physiological Sensors | Best Researcher Award 

Mr. Mohammad Ahmadi, University of Auckland, New Zealand

Ted Ahmadi is a seasoned game developer based in Toronto, with a strong focus on designing Mixed/Augmented/Virtual Reality (MR/AR/VR) games using Unity3D and C#. With over 6 years of experience, he is proficient in utilizing the Microsoft Mixed Augmented Reality Toolkit (MRTK) and has expertise in designing Mixed Reality games for platforms such as Magic Leap, Vive/Vive Pro Eye, Oculus Quest/Quest 2&3/Quest Pro, HP Omnicept, Hololens 2, and Apple Vision Pro. Ted’s career spans across various aspects of game development, including 2D game design for Android using Unity3D, game networking with Photon and Ubiq, and integrating technologies like OpenGL, Blender, and iClone 3D animation toolkit. He is also skilled in using Leap Motion for enhancing interactive experiences in game applications. Beyond game development, Ted is proficient in C++/C# programming across different applications and has experience in Agile/Rapid development methodologies, Waterfall, and Continuous Integration. His expertise extends to embedded systems such as ROS in Linux/Windows, particularly in VR applications for robotics, and enterprise web server applications where he excels in Java programming, software optimization, debugging, and troubleshooting.

Professional Profile:

ORCID

 

Education

University of Auckland

  • Bachelor of Science in Computer Science
    Date: Graduated in 2018

Work Experience

Design School, University of Auckland
Teaching and Tutoring Assistant
July 2022 – Nov 2022

  • Responsibilities: Assisted in teaching and tutoring the course “Designing Mix Realities” at the School of Design.
  • Skills: Unity3D, Blender (3D modeling and animation for rapid prototyping), Adobe Aero (3D modeling).

Skills

  • Game Design: Unity3D, MRTK and XR SDK, AR Kit, AR Core, Leap Motion, OpenGL, Vuforia, Blender, iClone 7.
  • Programming: C++/C#, Java, JavaScript, PHP/CSS/HTML, jQuery, mySQL, JSON/XML, Matlab.
  • HMD: Vive/Vive Pro Eye, Oculus Quest/Quest 2/Quest 3/Quest Pro, HP Omnicept, Magic Leap, Hololens 2, Apple Vision Pro.
  • API: WebGL, OpenGL.
  • Web API: .Net/ASP.Net MVC.
  • J2EE API: Java Servlet and EJB.
  • Version Control: git and GitHub.
  • OS: Linux, Windows.
  • Embedded Systems: ROS.

Employment History

🏫 Design School, University of Auckland
Teaching and Tutoring Assistant (July 2022 – Nov 2022)

  • Teaching and tutoring assistant for the course “Designing Mix Realities” at the school of design.
  • Skills: Unity3D, Blender (3D modeling and animation for rapid prototyping), Adobe Aero (3D modeling).

Publication top Notes:

EEG, Pupil Dilations, and Other Physiological Measures of Working Memory Load in the Sternberg Task

Cognitive Load Measurement with Physiological Sensors in Virtual Reality during Physical Activity

Comparing Performance of Dry and Gel EEG Electrodes in VR using MI Paradigms

PlayMeBack – Cognitive Load Measurement using Different Physiological Cues in a VR Game