Imran Saied

About

Dr. Imran Saied

Postdoctoral Researcher

imran.saied@kaust.edu.sa

RF & Microwave Sensing, RF & Microwave Imaging, Microwave Medical Imaging, Tomography Systems, Oil/Gas Monitoring


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ORCID: https://orcid.org/0000-0002-0204-0626
LinkedIN: https://www.linkedin.com/in/imran-saied
Google Scholar: ‪ ‪Imran Saied - ‪Google Scholar

About

Dr. Imran Saied is a Postdoctoral Researcher in the Integrated Microwaves Packaging Antennas and Circuits Technology (IMPACT) Research Group at King Abdullah University of Science and Technology (KAUST) led by Professor Atif Shamim.  

Research Interests

Dr. Imran’s research focuses on the design and development of various noninvasive imaging and monitoring systems, integrating various technologies (including, RF and microwave-based sensors) for real-world imaging applications in healthcare, advanced wearables, and oil/gas monitoring with a strong emphasis on developing and translating lab-scale innovations into functional prototypes. His work involves the design and fabrication of wearable and flexible RF sensors, investigation of microwave propagation or dielectric changes in various mediums, development of bespoke imaging/tomography algorithms, and implementing AI or machine learning to enhance classification of captured sensor data. In addition, he has also worked alongside clinicians, patients, and social scientists in an interdisciplinary capacity to incorporate co-design techniques into the development of various sensing systems for healthcare monitoring. His expertise spans tomography systems, RF sensing and imaging for healthcare applications, noninvasive multiphase flow systems, edge-AI, and quantum computing. 

           Education Profile

  1. Ph.D. Integrated Micro and Nano Systems, 2021, The University of Edinburgh, Edinburgh, UK.

  2. M.Sc. in Electrical Engineering, 2011, California State University, Fullerton, USA

  3. B.Sc. in Electrical Engineering, 2009, Georgia Institute of Technology, USA.

           Articles

  1. Saied, I.; Alzaabi, A.; Arslan, T. Unobtrusive Sensors for Synchronous Monitoring of Different Breathing Parameters in Care Environments. Sensors 2024, 24, 2233. https://doi.org/10.3390/s24072233

  2.  I. M. Saied, T. Arslan and S. Chandran, "Classification of Alzheimer's Disease Using RF Signals and Machine Learning," in IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology, vol. 6, no. 1, pp. 77-85, March 2022, https://doi.org/10.1109/JERM.2021.3096172

  3. I. Saied, T. Arslan, S. Chandran, et. al, "Non-Invasive RF Technique for Detecting Different Stages of Alzheimer’s Disease and Imaging Beta-Amyloid Plaques and Tau Tangles in the Brain," in IEEE Transactions on Medical Imaging, vol. 39, no. 12, pp. 4060-4070, Dec. 2020, https://doi.org/10.1109/TMI.2020.3011359.

  4. I. M. Saied and T. Arslan, "Noninvasive Wearable RF Device Towards Monitoring Brain Atrophy and Lateral Ventricle Enlargement," in IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology, vol. 4, no. 1, pp. 61-68, March 2020, https://doi.org/10.1109/JERM.2019.2926163

  5. I. M. Saied, S. Chandran and T. Arslan, "Integrated Flexible Hybrid Silicone-Textile Dual-Resonant Sensors and Switching Circuit for Wearable Neurodegeneration Monitoring Systems," in IEEE Transactions on Biomedical Circuits and Systems, vol. 13, no. 6, pp. 1304-1312, Dec. 2019, https://doi.org/10.1109/TBCAS.2019.2951500

  6. I. Saied and M. Mahmoud, "A New Imaging System for Real-Time Process Control," in IEEE Sensors Journal, vol. 17, no. 12, pp. 3844-3852, 15 June15, 2017, https://doi.org/10.1109/JSEN.2017.2697684

  7. I. M. Saied, M. Meribout, et. al., "Terahertz Spectroscopy for Measuring Multiphase Fractions," in IEEE Transactions on Terahertz Science and Technology, vol. 7, no. 3, pp. 250-259, May 2017,https://doi.org/10.1109/TTHZ.2017.2679602

  8. I. Saied and M. Meribout, "Electronic hardware design of electrical capacitance tomography systems", Philos. Trans. Roy. Soc. A Math. Phys. Eng. Sci., vol. 374, no. 2070, pp. 20150331, May 2016.

Patents

  1. Tughrul Arslan and Imran Saied, Fluid Monitoring System (Application no. WO2023242584A1) - WO2023242584A1 - Fluid monitoring system - Google Patents

Awards/Special Mentions

  1. Best Teacher Award (Shortlisted 2024) – Nominated by PhD students during course “Introduction to Interdisciplinary Research Methods and Techniques” taught at University of Edinburgh

  2. Presented invention (hydration monitoring cushion) to HRH Princess Anne (2023) - Chancellor gets to grips with ACRC | Usher Institute

  3. Alasdair Sutherland Award (2020) – Received award and funding for my PhD studies to conduct dielectric measurements of human brain tissue samples and develop realistic brain phantoms for various stages of Alzheimer’s disease in the brain.

  4. Best Lab Demonstrator/TA Award (2019) – Won Award for best lab demonstrator during my time mentoring students in Microelectronic Circuits, C++, and RF Design lab classes.

 

 

 

 

 

 

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