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FACULTY PROFILE

Engr. Dr. Shahabuddin Ansari

Assistant Professor
Email: sansari@giki.edu.pk
Qualifications: PhD, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Pakistan
Research Interests: Medical Image Processing and Analysis, Digital Signal Processing, Numerical Methods
Telephone: (Ext. 2554)
Website: http://http://www.giki.edu.pk/Faculty/Shahabuddin-Ansari

Summary


Dr. Shahab Ansari acquired Bachelor degree in Electronics from NED University, Pakistan, in 1987. Dr. Ansasri earned his Master degree in speech enhancement in hearing aids from McMaster University, Canada, in 2005. He completed his PhD in 2017 in numerically solving parabolic partial differential equations using stabilized mixed Galerkin method from Ghulam Ishaq Khan Institute of Engineering Sciences and Technology (GIKI), Pakistan. Currently, he is supervising various projects in Artificial Intelligence in Medicine (AIM) Lab and teaching undergraduate and graduate courses in the Faculty of Computer Science and Engineering in GIKI.

AIM Lab


Artificial Intelligence in Medicine (AIM) lab has been involved in quality research work in medical diagnostics and treatment using medical imaging and Artificial Intelligence (AI) since 2010. The lab has won a number of grants from Directorate of Science and Technology (DoST), KPK, and HEC, Pakistan. A grant of amount PKR480,000 from DoST was acquired for the implementation of automatic classification of prostate cancer tissues using wavelet packet transformation using histological images. Another project, on automatic segmentation of subcortical regions using nonlinear warping technique on brain MRIs was published in a FIT conference in 2010. In 2017, the lab also received a HEC grant of PKR452,300 for brain image analysis with tumors using AI techniques. Recently, a HEC-NRPU grant of PKR 1.1 million has been acquired for the characterization of Alzheimer's disease in MRI images using deep neural networks. The lab has also been involved in various digital image processing based and hardware-based final year projects for undergraduate students.

AIM Lab: https://sites.google.com/view/aimlab/home

Journal Publications & Conferences


N. Ali, S. U. Ansari, Z. Halim, R. H. Ali, M. F. Khan and M. Khan, "Breast Cancer Classification and Proof of Key Aritificial Neural Network Terminologies", 2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS), 2019.

M. Hussain,  S. U. Ansari, T. Manzoor,  A. Ahmad,  K. I. Khan"Performance Analysis of Parallel Stabilized Mixed Galerkin Method for Three-Dimensional Transient Darcy Flow using Mesh Reordering Techniques," Journal of Petroleum Science and Engineering2019

S. U. Ansari, M. Hussain, A. Rashid,  S. Mazhar, S. M. Ahmad, "Numerical Solution and Analysis of Three-Dimensional Transient Darcy Flow," Transport in Porous Media, 20-March, 2018. DOI:10.1007/s11242-018-1041-2.

S. U. Ansari, M. Hussain, A. Rashid, S. M. Ahmad, S. Mazhar, and K. J. Siddiqui, "Validating Numerical Solution of Transient Darcy Flow using Stabilized Mixed Finite Element Method," Simulation: Transactions of the Society for Modeling and Simulation International2017.

S. U. Ansari, M. Hussain, S. Mazhar, T. Manzoor, K. J. Siddiqui, M. Abid and H. Jamal, "Mesh Partitioning and Efficient Equation Solving Techniques by Distributed Finite Element Methods: A Survey," Archives of Computational Methods in Engineering2017.

S. U. Ansari, M. Hussain, S. M. Ahmad, A. Rashid and S. Mazhar, "Stabilized Mixed Finite Element Method for Transient Darcy Flow," Transactions of the Canadian Society for Mechanical Engineering, 41(1):85-97, 2017.

S. U. Ansari, M. Hussain, S. Mazhar, A. Rashid and S. M. Ahmad, "Parallel Stabilized Mixed Galerkin Method for Three-Dimensional Darcy Flow," NSEC, Islamabad, 2015.

S. U. Ansari, M. Hussain, S. Mazhar, A. Rashid and S. M. Ahmad, "Three-Dimensional Stabilized Mixed Galerkin Method for Darcy Flow," FIT, Islamabad, July, 2015.

S. U. Ansari, M. Hussain, S. Mazhar, A. Rashid and S. M. Ahmad, "Stabilized Mixed Galerkin Method for Transient Analysis of Darcy Flow," ICMSAO, Istanbul, Turkey, May, 2015.

F. Waqar, H. Qureshi, M. Hussain, S. U. Ansari, "Texture Classification using Discriminant Wavelet Packet Sub-bands and Support Vector Machines", WEC2013.

S. U. Ansari and S. Mansha. “Simulation-Based Hardness Evaluation of a Multi-Objective Genetic Algorithm.” ICOMS, Islamabad, 2013.

M. Abid,  A. Khan, S. U. Ansari. Selection of optimum girders (rolled section) for overhead cranes using finite element analysis. 9th International Conference on Fracture & Strength of Solids, Jeju, Korea. Pp. 1-5, 2013.

S. U. Ansari, "Validation of FS+LDDMM by automatic segmentation of caudate nucleus in brain MRI" Frontier of Information Technology (FIT), 2010.

S. U. Ansari and M. F. Beg, "Template-based brain MRI registration/segmentation using LDDMM with a priori spatial knowledge" Human Brain Mapping, 2007.

S. U. Ansari and M. F. Beg, "Template-based brain MRI segmentation using LDDMM" Neuroscience Extravaganza, 2006.

N. Harte, S. U. Ansari and I. Bruce, "Exploiting voicing cues for contrast enhanced frequency shaping of speech for impaired listeners," in Proceedings of 31st IEEE ICASSP, 2006.

S. U. Ansari, N. Harte and I. Bruce, "Efficiently combining improved contrast-enhancing frequency shaping and multiband compression to enhance speech intelligibility in hearing aids," LOAN Meeting, 2005.

S. U. Ansari, H. Bajaj, K. Mustafa and I. Bruce, "Time efficient contrast-enhancing frequency shaping and multiband compression in hearing aids," Abstracts of the IHCON, 2004.

I. Bruce, S. U. Ansari, H. Bajaj and K. Mustafa, "Multiband compression and contrast-enhancing frequency shaping in hearing aids," in Proceedings of the 2004 Annual Conference of the Canadian Acoustical Association2004.

Graduate Student Supervision


  1. Mr. Faizad Ullah, Master Student, Tumor Segmentation in Brain MRI using Convolution Neural Networks.

  2. Mr. Ahmad Raza, Master Student, Characterization of Alzheimer's Disease using Convolutional Neural Networks

  3. Mr. Muhammad Waqas, Master Student, Brain MRI Segmentation for the Identification and Classification of Schizophernia

  4. Mr. Najam Ur Rahman, Master Student, Brain MRI segmentation for the classification of Multiple Sclerosis using Machine Learning Techniques

  5. Mr. Hafiz Owais, Master Student, Ai-Based Prediction Model for the Diagnosis and Treatment of a Disease

 

Graduate Student Co-Supervision


  1. Mr. Salman Mehboob, Master student, GIK Institute, Video Surveilance and Tracking. (Expected to graduate in 2018)
  2. Mr. Fahad Waqar, Master student, GIK institute, Automation of Gleason Grading using Wavelet Packet Transform. (Graduated & Published in WEC, 2013)
  3. Mr. Usman Ali, Master Student, Automatic Cancerous Tissue Classification. (Graduated in 2014)
  4. MS Sidra, PhD Scholar (UET Peshawar), Automatic Liver Tumor Segmentation using Deep Learning Techniques. (REC Committee)

PSF Proposal


Minimizing diagnostic errors, reducing doctor-patient time, prescribing accurate treatment in clinics is a heavenly idea. Today, the idea could become reality using artificial intelligence and medical image processing techniques in clinical practice. These advanced technologies would assist physicians/surgeons in diagnosis and prognosis of a disease, accurate treatment procedure and surgical planning. The treatment can also be made smarter by introducing data analytics approach on the demography of a region. In case of referral, the complete patient information can also be made available remotely to other medical experts on one click. So, an intelligent and easy-to-use system that assures accuracy and efficiency in decision making for patient care in clinics is what being proposed here.



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