Seyed Hossein Mirjahanmardi received his Ph.D. from the University of Waterloo, Canada, in 2020 with honors. His research and industrial experience span from Electromagnetics and RF design to Pathology Image Analysis using Artificial Intelligence algorithms.

Honors & Awards

  • Outstanding Teaching Sandford Fleming Award, University of Waterloo (2019)
  • Ontario PhD Nomination Award, Ontario (2020)
  • IEEE Senior Member, IEEE (2022)
  • Best Teaching Assistant Award, University of Waterloo (2018)
  • Best Thesis Presentation Award, University of Waterloo (2018)
  • Best Student Award, University of Waterloo (2017)
  • Best Student Award, University of Waterloo (2016)
  • Best Student Award, Amirkabir University of Technology (2014)
  • 3MT Finalist, University of Waterloo (2018)

Professional Education

  • Ph.D., University of Waterloo, Electrical and Computer Engineering (2020)

Stanford Advisors


  • Seyed Hossein Mirjahanmardi, Omar Ramahi. "United States Patent 62909218 Computerized Tomography with Microwaves", Oct 1, 2019

All Publications

  • Toward Computerized Tomography With Microwaves IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES Mirjahanmardi, S., Ramahi, O. M. 2022
  • Permittivity Characterization of Dispersive Materials Using Power Measurements IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT Mosavirik, T., Soleimani, M., Nayyeri, V., Mirjahanmardi, S., Ramahi, O. M. 2021; 70
  • Permittivity Reconstruction of Nondispersive Materials Using Transmitted Power at Microwave Frequencies IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT Mirjahanmardi, S., Albishi, A. M., Ramahi, O. M. 2020; 69 (10): 8270-8278
  • Intelligent Sensing Using Multiple Sensors for Material Characterization SENSORS Albishi, A. M., Mirjahanmardi, S. H., Ali, A. M., Nayyeri, V., Wasly, S. M., Ramahi, O. M. 2019; 19 (21)


    This paper presents a concept of an intelligent sensing technique based on modulating the frequency responses of microwave near-field sensors to characterize material parameters. The concept is based on the assumption that the physical parameters being extracted such as fluid concentration are constant over the range of frequency of the sensor. The modulation of the frequency response is based on the interactions between the material under test and multiple sensors. The concept is based on observing the responses of the sensors over a frequency wideband as vectors of many dimensions. The dimensions are then considered as the features for a neural network. With small datasets, the neural networks can produce highly accurate and generalized models. The concept is demonstrated by designing a microwave sensing system based on a two-port microstrip line exciting three-identical planar resonators. For experimental validation, the sensor is used to detect the concentration of a fluid material composed of two pure fluids. Very high accuracy is achieved.

    View details for DOI 10.3390/s19214766

    View details for Web of Science ID 000498834000163

    View details for PubMedID 31684027

    View details for PubMedCentralID PMC6864703

  • Forward Scattering from a Three Dimensional Layered Media with Rough Interfaces and Buried Object(s) by FDTD APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY JOURNAL Mirjahanmardi, S. H., Dehkhoda, P., Tavakoli, A. 2017; 32 (11): 1020-1028