Ali Imran Sandhu (Member, IEEE) received the B.S. degree in electronics engineering from COMSATS University Islamabad (CUI), Lahore, Pakistan, in 2007, the M.S. degree in communication engineering from the Chalmers University of Technology, Gothenburg, Sweden, in 2010, and the Ph.D. degree in electrical engineering from the Division of Computer, Electrical, and Mathematical Sciences and Engineering, King Abdullah University of Science and Technology, (KAUST), Thuwal, Saudi Arabia, in 2020.,From 2011 to 2013, he was a Research Engineer with the Microwave Laboratory, University of Calabria, Rende, Italy. From August 2007 to September 2021, he was a Lecturer with the Electrical and Computer Engineering Department, CUI, where he taught at undergraduate and graduate levels. He is currently a Postdoctoral Fellow with the Center of Integrative Petroleum Research, King Fahd University of Petroleum and Minerals (KFUPM). His research interests include applied computational electromagnetics with an emphasis on the characterization of electromagnetic fields and wave interactions on complex geometries, and solutions for 2-D and 3-D joint EM and seismic inverse problems incorporating signal processing and machine learning techniques, integration of physics informed machine learning with numerical wave propagation solvers and Bayesian experimental design for efficient sensor placement in an imaging framework.
He was the Finalist in the Student Poster Competition at the IEEE IST Conference, in 2016, and secured the Best Student Paper Nomination at the IEEE Applied Computational Electromagnetics Society Conference, in 2017. He received two Bronze medals for securing distinction in his undergraduate discipline at the campus as well as at institute levels at CUI.
1. A. I. Sandhu, B. D. Mansour, O. Dorn and P. Soupios, “Bayesian Experimental Design for Efficient Sensor Placement for Two-
Dimensional Electromagnetic Imaging”,in IEEE Access, vol. 11, pp. 65649-65662, 2023.
2. A. I. Sandhu, U. Waheed, O. Dorn and P. Soupios, “Multifrequency Wavefield Modeling of Acoustic VTI Wave Equation Using
Physics Informed Neural Networks”, accepted for publication at Frontiers in Earth Science, Solid Earth Geophysics, 2023
3. A. I. Sandhu, A. Desmal, S. A. Shaukat and H. Bagci, “A Neural Network Assisted Greedy Algorithm For Sparse Electromagnetic
Imaging”, IEEE Trans. Antennas Propag., vol. 69, no. 9, pp. 6093-6098, Sept. 2021
4. A. I. Sandhu, A. Desmal and H. Bagci, “An Accelerated Nonlinear Contrast Source Inversion Scheme for Sparse ElectromagneticImaging”, in IEEE Access, vol. 9, pp. 54811-54819, 2021.
5. A. I. Sandhu, e.t. al, “Radiating elements for shared aperture Tx/Rx phased arrays at K/Ka band”, IEEE Trans. Antennas Propag.,
vol. 64, no. 6, pp. 2270–2282, 2016
1. A. I. Sandhu, B. D. Mansour, O. Dorn and P. Soupios, “Bayesian Experimental Design For Efficient Sensor Placement In Electromagnetic
Geophysical Exploration”, submitted to International Petroleum Technology Conference (IPTC) 2023, Dhahran KSA
2. A. I. Sandhu, U. Waheed, O. Dorn and P. Soupios, “Multifrequency seismic wavefield modeling in anisotropic media using
physics-informed neural networks”, accepted for oral presentation at SEG IMAGE 2023 conference, August 2023, Houston Texas
3. A. Miftakhutdinov, U. Waheed, A. I. Sandhu, K. Shukla and G. Karniadakis, “JAXcelerate Seismic Full Waveform Inversion : A
High-Performance Approach to PINN- based FWI”, accepted for oral presentation at SEG IMAGE 2023 conference, August 2023,
4. A. I. Sandhu, A. Desmal and H. Bagci, “A Self-Adaptive Accelerated Contrast Source Inversion Scheme for Nonlinear Electromagnetic
Imaging”, In. Proc. IEEE International Conference on Imaging Systems and Techniques (IST), (Best Student Poster Finalist),
December 2019, AbuDhabi
5. A. I. Sandhu, S.A. Shaukat, A. Desmal and H. Bagci, “A Machine Learning Assisted Compressive Sensing Approach for Sparse
Electromagnetic Imaging”, In. Proc. IEEE International Conference on Computational Electromagnetics (ICCEM), March 2020, Singapore
6. A. Desmal, A. I. Sandhu and H. Bagci, “Nonlinear Projected Sparse Optimization Approach Based on Adam Algorithm for Microwave
Imaging”, In. Proc. Advances in Science and Engineering Technology multi-conferences (ASET), December 2019, AbuDhabi
7. A. I. Sandhu, A. Desmal and H. Bagci, “An Accelerated Contrast Source Inversion Scheme For Nonlinear Electromagnetic Imaging”,
In proc. Progress In EM Research (IEEE PIERS). Toyama, Japan
8. A. I. Sandhu and H. Bagci, “A Modified CoSaMP Algorithm For Electromagnetic Imaging of Two Dimensional Domains”, In proc.
International Applied Computational Electromagnetics Society Symposium (IEEE ACES), (Best Student Paper Finalist), Florence,
9. A. I. Sandhu, A. Desmal and H. Bagci, “A Projected Steepest Descent Accelerated Contrast- Source Inversion Scheme for Nonlinear
Electromagnetic Imaging”, In proc. IEEE International Symposium on Antennas and Propagation and Radio Science Meeting
(APS-URSI). San-Diego, U.S
10. A. I. Sandhu, A. Desmal and H. Bagci, “A Sparsity-Regularized Born Iterative Method for Reconstruction of Two-Dimensional
Piecewise Continuous Inhomogeneous Domains”, In proc. IEEE EuCAP, Davos, Switzerland
11. A. I. Sandhu, A. Desmal and H. Bagci, “A Sparsity Regularized In-Exact Newton Method for the Reconstruction of Two Dimensional
Inhomogeneous Domains”, In proc. IEEE APS-URSI, Puerto Rico, U.S
12. Y. Shi, A. I. Sandhu, e.t. al, “Analysis of Transient Electromagnetic Wave Interactions on Graphene Sheets Using Integral Equations”,
In proc. IEEE APS-URSI, Vancouver, Canada.
12. L. Boccia, A. Shamsafar, E. Arnieri, A. I. Sandhu, e.t. al, “SiGe BiCMOS technology for Ka-band satcom on the move user terminals”,
In proc. IEEE EuCAP, Hague, Netherlands
13. F Greco, G Amendola, E Arnieri, L Boccia, and A. I. Sandhu, “A dual-band, dual-polarized array element for Ka band satcom on
the move terminals”, In proc. IEEE EuCAP, Hague, Netherlands