Faculty Img
  • Phone:

    +966-13-849-5414

  • Email:

    akhan@pmu.edu.sa

  • Office No:

    S-008

  • Engr. Adil Humayun Khan

  • Job Title :

    Lab Instructor

  • College :

    College of Engineering


  • Department :

    Electrical Engineering


Secured Bachelor’s degree in Electrical Engineering from COMSATS University Lahore, Pakistan in 2008, as a Gold Medalist. Degree of MS in Electrical Engineering was secured from King Fahd University of Petroleum and Minerals in 2013. I have experience in mostly used electrical engineering software e.g. Matlab, Labview, Multisim and Pspice, also having experience in industrial field software used in RF Planning such as TEMS and Mapinfo. I worked as Lab Engineer in COMSTAS Institute of Information and Technology Lahore and also designed the lab for Wireless Communication Systems. I have done work as RF Engineer at ACE Telecom, which was the sub-contractor of Etisalat. Since 2013, I have been part of PMU faculty. My research interests are in Signal and image processing, currently I am an active member of “BIOMEDICAL SIGNAL/IMAGE PROCESSING” research group in PMU. I have done work on image despeckling, segmentation and classification.

 

MS Electrical Engineering

 

Journal Publications

  • [J-5]     Recent advancements in Fuzzy C-means based techniques for brain MRI Segmentation, Current Medical Imaging, 2021 Jan 3.

  • [J-4]   QR based Despeckling Approach for Medical Ultrasound Images, CMIR, August 2018

  • [J-3]   A Hybrid Particle Swarm Optimization Technique for Adaptive Equalization, Arabian Journal for Science and Engineering, 2018, pp 1-8

  • [J-2]   Deep CNN based MR image denoising for tumor segmentation using watershed transform, International Journal of Engineering and Technology, March 2018, Volume 7 (No 2.3)
  • [J-1]   Speckle Suppression in Medical Ultrasound Images through Schur Decomposition, IET journal on image Processing, 2017

Conference Publications

  • [C-10] Spectral Decomposition By Schur for Medical Ultrasound Image Denoising, IEEE International Symposium on Advanced Electrical and Communication Technologies (ISASET), Rome, Italy, November 2019
  • [C-9]    Ultrasound Image Denoising Using Orthogonal Decomposition in Frequency Domain, 9th IEEE International Conference on System Engineering and Technology (ICSET), Malaysia, October 2019.
  • [C-8] Adil H. Khan, D.N.F. Awang Iskandar, Jawad F. Al-Asad, "Classification of Skin Lesion with Hair and Artifacts Removal Using Black-Hat Morphology and Total Variation".
  • [C-7] Segmentation of Melanoma Skin Lesions using Anisotropic Diffusion and Adaptive Thresholding, 8th International Conference on Biomedical Engineering and Technology (ICBET 2018) Proceedings, Indonesia
  • [C-6] QR based De-noising Scheme for Medical Ultrasound Images, 9th IEEE GCC Conference & Exhibition, May 2017, Manama, Bahrain.
  • [C-5] Automatic Multimodal Brain Image Classification using MLP and 3D Glioma Tumor Reconstruction, 9th IEEE GCC Conference & Exhibition, May 2017, Manama, Bahrain.
  • [C-4] Multiclass Brain Glioma Tumor Classification using Block-based 3D Wavelet Features of MR Images, 4th International Conference on Electrical and Electronics Engineering, April 2017, Ankara, Turkey.
  • [C-3] IoT based Real-time Voice Analysis and Smart Monitoring System for Disabled People, 1st International Conference on Advanced Research (ICAR -2017), Bahrain.
  • [C-2] Eye Click: Eye Gazed Based User Interface for the Disabled People, International Conference on Technology for Helping People with Special Needs, ICTHP-2013.
  • [C-1] Application of a PSO algorithm in adaptive equalization using adaptive inertia weights, The Fourth Scientific Conference for Students of Higher Education in K.S.A, 2013.

Google Scholar Link

 

https://scholar.google.com/citations?user=j0FDz1UAAAAJ&hl=en

 

Research Gate Link

https://www.researchgate.net/profile/Adil-Khan

 

 

 

 

In Image Processing Despeckiling of Ultrasound images, Segmentation and classification of Skin lesion and brain MR images.

 

 

IEEE