Dr. Abdulla Desmal

Areas of Research Interest

Machine learning, electromagnetic modeling, X-ray Compton imaging, radiation therapy planning, inverse scattering, inverse problems, nonlinear optimization, and image processing.
Research Statement
My research journey has been anchored in three key pillars, each contributing to the advancement of imaging, modeling, and therapy planning within the realm of electromagnetic wavefields, acoustic wavefields, X-rays, and static electric charges. By integrating novel imaging algorithms and machine learning approaches, I have consistently aimed to achieve higher contrast resolution and enhanced image characterization.

Design Research or Scholarship Agenda

1. Building Novel Imaging Algorithms
   In the domain of electromagnetic imaging, my focus has been on developing forward and inverse algorithms, enriched by machine learning schemes. The algorithms, tailored for both two and three-dimensional sparse domains, have undergone rigorous testing with real data measurements. Employing Matlab and Fortran-90 MPI parallel programming, augmented by GPU accelerators for machine learning modeling, the schemes have demonstrated promising results in various applications, including tumor detection, through-wall imaging, and crack detection.

   Evidence in the portfolio includes detailed examinations of the approach’s range of validity under supercomputers/clusters at prestigious institutions like KAUST and Tufts University. The sophistication of the inversion schemes is evident through the adoption of advanced modeling techniques, such as Convolutional Neural Networks, FFT matrix multiplication, and multipole expansion along sparse matrix optimization. The portfolio also highlights the successful application of stabilized Biconjugate gradient algorithms to address ill-posed inversions, both within linear and nonlinear frameworks, using novel sparse optimization approaches.

2. X-ray Imaging Advancements
   Collaborating with Tufts University, my research has focused on the development of next-generation X-ray scanners, particularly for airport luggage screening. The novelty lies in inverting data from both transmitted X-rays and Compton scattered rays. This innovative approach significantly enhances material characterization, thereby reducing false alarm rates and distinguishing a broader range of materials. The accelerated forward model, coded using parallel Matlab scripts, has been successfully executed on the Tufts cluster/supercomputer. The higher contrast imaging achieved through this approach not only has implications for luggage screening but also holds promise in the biomedical imaging field, particularly for early tumor detection.
3. Novel Therapy Planning Approaches:
   In collaboration with Duke University, my research endeavors focus on the development of novel treatment approaches for multi-form tumors within the realm of radiation oncology. The objective is to design methods that deliver high-energy doses to tumor volumes while sparing normal tissues.

In conclusion, my research endeavors not only aim to contribute to the theoretical understanding of imaging and therapy planning but also anticipate the evolving needs of the scientific community and society at large. Through continuous innovation, collaboration, and mentorship, I am dedicated to shaping a future where our contributions leave a lasting impact on the field of electrical engineering and beyond.ssistants, who contribute to field studies, data collection, and practical testing of developed frameworks.

• A. Desmal, “Technological Advances in Smart Monitoring Imaging Systems Based on Machine Learning.”, CRC Press Taylor & Francis, 2023.

Journals

• A. Desmal and J. Alsaei. “Multi-frequency trained projection nonlinear framework for electromagnetic imaging with contrast-source Landweber-Kaczmarz,” IEEE Trans. Geosci. Remote Sens. Lett., May, 2024.
• A. Desmal, “A Trained Iterative Shrinkage Approach Based on Born Iterative Method for Electromagnetic Imaging.” IEEE Transactions on Microwave Theory and Techniques. V70, I11, pp 4991-4999, March. 2022.
• A. Desmal, ” A Contrast-Source Electromagnetic Imaging Scheme Based on Projected Nonlinear Landweber-Kaczmarz”. IEEE Trans. Antennas Propag., V70, I9, pp 8666 – 8670, March 2022.
• A. Desmal, “High-Quality Self-Contained Electromagnetic Imaging Scheme Based on Projected Nonlinear Landweber and Machine Learning”. IEEE Trans. Antennas Propag., V 70, I2, pp 1380-1388, Feb. 2021.
• S., A. Imran, A. Desmal, and H. Bagci. “An accelerated nonlinear contrast source inversion scheme for sparse electromagnetic imaging.” IEEE Access V9 (2021): P54811-54819.‏
• Sandhu, A. I., Shaukat, S., A. Desmal, A., & Bagci, H. (2021). “ANN-assisted CoSaMP Algorithm for Linear Electromagnetic Imaging of Spatially Sparse Domains. ” IEEE Transactions on Antennas and Propagation.‏ V69, I9 P6093 – 6098.
• A. Desmal, et al. “Limited-View X-Ray Tomography Combining Attenuation and Compton Scatter Data: Approach and Experimental Results.” IEEE Access 7 (2019): 165734-165747.
• A. Desmal and H. Bagci, “Sparse Nonlinear Electromagnetic Imaging Accelerated with Projected Steepest Descent Algorithm,” IEEE Trans. Geosci. Remote Sense., 55.7 (2017): 3810-3822.
• A. Desmal and H. Bagci, “Sparse electromagnetic imaging using nonlinear Landweber iterations,” Progress In Electromagnetics Research, vol. 152, pp. 77-93, July, 2015.
• A. Desmal and H. Bagci. “A Preconditioned inexact Newton method for nonlinear sparse electromagnetic imaging,” IEEE Trans. Geosci. Remote Sens. Lett., vol. 12, no. 03, pp. 532-536, March, 2015.
• A. Desmal and H. Bagci, “Shrinkage-thresholding enhanced Born iterative method for solving 2D inverse electromagnetic scattering problem,” IEEE Trans. Antennas Propag., vol. 63, no. 07, pp. 3878-3884, July, 2014.

 Conferences

• M. Almansoori, S. Alshehhi, S. Aljasmi, S. Albastaki, M. Altenaiji, N. Galupa, A. Abdulkhadar, & A. Desmal. ” Circuit Implementation for Voltage Signal Extraction in Electrical Impedance Tomography “. In 2024 Advances in Science and Engineering Technology International Conferences (ASET), 2024. IEEE.‏
• N. Alshehhi, A. Almansoori, H. Alshehhi, Y. Alsuwaidi, A. Alnaqbi, N. Nabeel, N. Galupa, A. Abdulkhadar, & A. Desmal. ” Developing Current Injection Circuit for Electrical Impedance Tomography”. In 2024 Advances in Science and Engineering Technology International Conferences (ASET), 2024. IEEE.‏
• K. A. Alshehhi, M. A.  Salem, A. Abdulkadar, N. Galupa, A. Parackal, A. Khodary, & A. Desmal. “Low-Cost Three-Dimensional Surface Recovery Scanner for Fine-Detailed Objects”. In 2023 Advances in Science and Engineering Technology International Conferences (ASET) (pp. 1-6). IEEE.‏
• A. Desmal. “Trained Electromagnetic Imaging Approach based on Born Iterative Method”. In 2023 Advances in Science and Engineering Technology International Conferences (ASET) (pp. 1-3). IEEE.‏
• A. Desmal. “A Contrast-Source Inversion Approach Base on Projected Landweber-Kaczmarz.” 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI). IEEE, 2022.‏
• K. Alshehhi, M. Almansoori, M. Alnaqbi, Y. Aljewari, A. Desmal, 2022. Mask and Helmet Detection using Transfer Learning. In 2022 Advances in Science and Engineering Technology International Conferences (ASET) (pp. 1-4). IEEE.
• Y. Moumouni, N. Galupa, A. Desmal, S. Mishra, M. Gdeisat, S. Ali, A. Khodary, 2022. Performance of a Stand-Alone Photovoltaic System: An energy sharing approach. In 2022 Advances in Science and Engineering Technology International Conferences (ASET) (pp. 1-4). IEEE.
• A. Desmal, (2020, December). “Deep Learning Enhanced Electromagnetic Imaging Scheme”. In 2020 International Conference on Innovation and Intelligence for Informatics, Computing and Technologies (3ICT) (pp. 1-4). IEEE.‏
• A. Desmal, Sandhu, A.I. and Bagci, H., 2020. Nonlinear Projected Sparse Optimization Approach Based on Adam Algorithm for Microwave Imaging. In 2020 Advances in Science and Engineering Technology International Conferences (ASET) (pp. 1-4). IEEE.
• Gdeisat, M., A. Desmal, Moumouni, Y., Al-Aubaidy, Z. S., Al Khodary, A., Hindash, A., & Wavegedara, C. Kernel Symmetry for Convolution Neural Networks. In 2020 Advances in Science and Engineering Technology International Conferences (ASET) (pp. 1-3). IEEE.
• A. Desmal, Sheng, Y., Stephens, H., Ge, Y., Wu, Q., & Wu, J. (2019, March). Two-Photon Dose Engines for Accurate and Fast Volumetric Modulated Arc Therapy. In 2019 Advances in Science and Engineering Technology International Conferences (ASET) (pp. 1-4). IEEE.
• A. Desmal, Y. Ge, and Q. Wu. “Fast Two-Step Inverse Planning Approach for Volumetric Modulated Arc Therapy.” MEDICAL PHYSICS. Vol. 45. No. 6. 111 RIVER ST, HOBOKEN 07030-5774, NJ USA: WILEY, 2018.
• A. Desmal, B. Tracey and E. Miller “Sparse view Compton scatter tomography with energy-resolved data: experimental and simulation results.” SPIE Defense+ Security. International Society for Optics and Photonics, 2017.
  Invited talk to SPIE conference on 2017, Defense+Security, Los-Anglos, California-USA
• A. Sandhu, A. Desmal and H. Bagci, “A sparsity-regularized Born iterative method for reconstruction of two-dimensional piecewise-continuous inhomogeneous domains”, European Conf. Antennas Propag., Davos, Switzerland, April, 2016
• A. Desmal and H. Bagci, “Three-dimensional sparse electromagnetic imaging accelerated by projected steepest descent.” Int. Symp. Antennas Propagat., Puerto Rico, US, July, 2016.
• A. Desmal and H. Bagci, “A sparse electromagnetic imaging scheme using nonlinear Landweber iterations,” Int. Symp. Antennas Propagat. USNC-URSI Radio Sci., VC, Canada, Jun, 2015
• A. Desmal and H. Bagci, “Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding,” European Conf. Antennas Propag., Lisbon, Portugal, April, 2015
• A. Desmal and H. Bagci, “Sparse electromagnetic reconstruction via iterative shrinkage thresholding algorithms,” Appl. Computational Electromagnetic Soc., Jacksonville, Florida, US, March 2014.
• A. Desmal and H. Bagci, “Nonlinear microwave imaging using Levenberg-Marquardt method with iterative shrinkage thresholding,” Int. Symp. Antennas Propagat. USNC-URSI Radio Sci., Memphis, TN, US, July 2014.
• A. Desmal and H. Bagci, “Sparse contrast-source inversion using linear-shrinkage-enhanced inexact Newton method,” Int. Symp. Antennas Propagat., Memphis, TN, US, July 2014. Selected among 10 best papers out of 160 papers, APS-URSI student competition, Memphis TN-USA
• A. Desmal and H. Bagci, “Comparison of various sparsity-regularized gradient-based algorithms for solving 2D electromagnetic inverse scattering problem,” Progress in Electromagnetic Research Symp., KL, Malaysia, March 2012

1. Chair of the International Bioengineering Conference under ASET multi-conference, Dubai, since 2021