NextGen Center Academic Director, Associate Professor

BSc   (honor) in Computer Science, University of Sharjah, Sharjah, UAE.
MSc   (honor) in Computer Science, University of Sharjah, Sharjah, UAE.
Ph.D  Computer Engineering, Khalifa University, Abu Dhabi, UAE.


Dr. Fatma Taher is an Associate Professor in the department of computer and applied technology and an assistant dean for Research and Outreach in the College of Technological Innovation and the CEO of Happiness and Wellbeing at Zayed University, Dubai, UAE. Her research interests are in the areas of signal and image processing, pattern recognition, artificial intelligent, medical image analysis, especially in detecting of the cancerous cells, kidney transplant, autism and Cerebrovascular Segmentation from MRA Images. In addition to that, remote sensing and satellite images researches. She received her PhD from Khalifa University of Science, Technology and Research, UAE, in 2014. So that she is the first UAE local that graduated with PhD in Engineering inside the UAE, and Khalifa University considered as the first University to grant PhD degrees in computer engineering. Dr. Fatma Taher has published more than 100 papers in international Journals and conferences. She served as a member of the steering, organizing and technical program committees of many international conferences, and has served on many editorial and reviewing boards of international journals and conferences. In 2021, she was the General Chair for the high raked and flagship conference ICECS 2021: 28th IEEE International Conference on Electronics, Circuits, and Systems (ICECS), 28th Nov- 1st Dec. 2021, Dubai, UAE. Dr. Fatma is the chair of IEEE UAE section since 2019.

Dr. Fatma has received many distinguished awards such as: the UAE Pioneers award as the first UAE to create a computer aided diagnosis system for early lung cancer detection based on the sputum color image analysis, awarded by H.H Sheik Mohammed Bin Rashed Al Maktoum, 15th Nov. 2015. Innovation award at the 2016 Emirati Women Awards by H. H. Sheik Ahmed Bin Saeed Al-Maktoum. Chairman of Civil Aviation Authority and Patron of Dubai Quality Group and L’Oréal-UNESCO For Women In Science Middle East Fellowship 2017. In addition to that, the Prize for the best PhD excellence Award in leadership day for Khalifa University, 12th February 2012. Best paper award in the BCS International IT Conference Towards 21st Century Innovations, Abu Dhabi, UAE, 31st March-1st April 2013. Best paper award of the first prize in the PhD Forum of the 20th IEEE International Conference on Electronics, Circuits, and Systems (ICECS), PhD Forum, Dec. 8-11, 2013. Dr. Fatma has developed new techniques for the accurate identification and segmentation of medical images (MRI, CT images) as well as new registration techniques based on multiple second-order signal statistics, all of which have been reported at multiple international conferences and journal articles. On 8th September 2020, Dr. Fatma Taher has registered a USA patent titled: Cerebrovascular Segmentation from MRA Images”, USA – Patent Application granted by United States Patent and Trademark Office (USPTO) under the number : 10768259.Grant,


Dubai Academic City, R-L1-067


+9714 402 1712

Teaching Areas

Signal and Image Processing, Medical Image analysis, Machine learning, Cloud computing, Artificial Intelligence, innovation and Entrepreneurship, Data Mining, Pattern recognition, remote sensing. Database Application, Software Engineering, Computer Network, Graphics, Operating Systems, Compiler Design, Design Analysis of Algorithms, File processing and Data management. Programming (C, Pascal, Prolog , Assembly , HTML ,Visual Basic, Visual Studio C++ , open GL, Java and MATLAB )

Research and Professional Activities

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Research and Professional Activities (last 5 years)


Refereed journal papers

  1. F. Taher, Naoufel Werghi, Hussain Al-Ahmad and Christian Donner, “Extraction and Segmentation of sputum cells for Lung Cancer Early Diagnosis”, Algorithms Journal of Machine Learning for Medical Imaging, pp. 512-531, vol. 6, August 2013.
  2. F. Taher, Naoufel Werghi and Hussain Al-Ahmad, “Computer Aided Diagnosis System for Early Lung Cancer Detection”, Algorithms, vol. 8, no. 4, pp. 1088-1110, Nov. 2015.
  3. A. Shalaby, F. Taher, M. El-Baz, M. Ghazal, M. Abou El-Ghar, and A Taqieldeen, and A. El-Baz, "Probabilistic Modeling of Blood Vessels for Segmenting Magnetic Resonance Angiography Images," Medical Research Archives, vol. 5, no. 6, March 2017,
  4. A. Shaffie, A. Soliman, M. Ghazal, F. Taher, N. Dunlap, B. Wang, V. Van Berkel, G. Gimel’farb, A. Elmaghraby, and A. El-Baz, “A Generalized Deep Learning Based Diagnostic System for Early Diagnosis of Various Types of Pulmonary Nodules,” Technology in Cancer Research & Treatment Journal, 2018.
  5. A. Shaffie, A. Soliman, M. Ghazal, F. Taher, N. Dunlap, B. Wang, V. Berkel, G. Gimelfarb, A. Elmaghraby, and A. El-Baz, "Lung Nodule Classification based on the Integration of Higher Order MGRFAppearance Model and Geometric Features", Technology in Cancer Research & Treatment, 2018. (in press).
  6. M. Shehata, F. Khalifa, A. Soliman, M. Ghazal, F. Taher, M. El-Ghar, A. Dwyer, G. Gimel'farb, R. Keynton and A. El-Baz, “Computer-Aided Diagnostic System for Early Detection of Acute Renal Transplant Rejection Using Diffusion-Weighted MRI”, IEEE Transactions on Biomedical Engineering, vol. 66, no. 2, pp. 539-552, Feb. 2019, 10.1109/TBME.2018.2849987
  7. F. Taher, A. Soliman, H. Kandil, A. Mahmoud, A. Shalaby and A. El-Baz, “Cerebrovascular Segmentation from MRA Images”, IEEE Transaction on Biomedical Engineering, in press, July 2019.
  8. H. Abdeltawab, F. Khalifa, F. Taher, G. Beache, T. Mohamed, R. Keynton, and A. El-Baz, “A Deep Learning-Based Approach for Automatic Segmentation and Quantification of the Left Ventricle from Cardiac Cine MR Images”, submitted to the Computerized Medical Imaging and Graphics (under review), Dec. 2019.
  9. Alkadi. R, Elbaz. A, F. Taher, N. Werghi, “A 2.5D deep learning-based approach for prostate cancer detection on T2-weighted magnetic resonance imaging”, Lecture Notes in Computer Science, Volume 11132 LNCS, Pages 734-739, 2019.
  10. R. Alkadi, F. Taher, A. El-Baz, and N. Werghi, “A Deep Learning-Based Approach for the Detection and Localization of Prostate Cancer in T2 Magnetic Resonance Images,” Journal of Digital Imaging, pp. 793-807, vol. 32, no. 5, 2019.
  11. H. Kandil, A. Soliman, F. Taher, M. Ghazal, A. Khalil, G. Giridharan, R. Keynton, J. R. Jennings, and A. El-Baz, “A novel computer-aided diagnosis system for the early detection of hypertension based on cerebrovascular alterations,” NeuroImage: Clinical, Elsevier, p. 102107, vol. 25, 2019.

Papers in refereed conference proceedings

  1. F. Taher, Naoufel Werghi and Hussain Al-Ahmad, “Rule Based Classification of Sputum Images for Early Lung Cancer Detection”, proceeding of the 22nd IEEE International Conference on Electronics, Circuits, and Systems (2015 ICECS), pp. 29-32, Cairo, Egypt, Dec. 06-09, 2015.
  2. F. Taher, A. Kunhu and H. Al-Ahmad, “A New Hybrid Watermarking Algorithm for MRI Medical Images using DWT and Hash Functions”, proceeding of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Lake Buena Vista (Orlando), Florida USA, pp. 1212 - 1215, 16-20 August 2016.
  3. F. Taher, A. Zaki and H. Elsimary, “Design of Low Power of Image Unit for Satellite Camera System”, proceeding of the 2016 IEEE 59thMidwest Symposium on Circuits, pp. 249-252, Abu Dhabi, UAE, 16-19 Oct. 2016.
  4. F. Taher, A. Soliman, A. Mahmoud, A. Shalaby and A. El-Baz, “A New 3D Appearance Model for Accurate Segmentation of Brain Vascular System”, proceeding on the Biomedical Engineering Society BMES 2018 Annual Meeting, Oct. 17-20 ,2018, Atlanta, Georgia, USA.
  5. F. Taher, A. Mahmoud, A. Shalaby, and A. El-Baz, "A Review on the Cerebrovascular Segmentation Methods," In: Proceedings of IEEE International Symposium on Signal Processing and Information Technology (ISSPIT'18), pp. 359-364, Louisville, KY, USA, Dec 6-8, 2018.
  6. A. Shaffie, A. Soliman, F. Taher, N. Dunlap, B. Wang, A. Elmaghraby, G. Gimel’farb and A. El-Baz, “A new Framework for Incorporating Appearance and Shape Features of Lung Nodules for Precise Diagnosis of Lung Cancer”, proceeding at IEEE International Conference on Image Processing (ICIP) conference, pp. 1372-1376, China, Sept. 17-20, 2017.
  7. A. Elshamekh, F. Taher, O. Dekhil*, G. M. Beache, H. Al-ahmad, and A. El-Baz, "Deep Learning Semi-Automated Heart Ventriculometrics Estimation", In Biomedical Engineering Society Annual Scientific Meeting (BMES'17), Phoenix, Arizona, USA, October 11-14, 2017.
  8. A. Shaffie, A. Soliman, M. Ghazal, F. Taher, N. Dunlap, B. Wang, V. Van Berkel, G. Gimel’farb, A. Elmaghraby, and A. El-Baz, “A Novel Autoencoder-Based Diagnostic System for Early Assessment of Lung Cancer,” In: Proc. IEEE International Conference on Image Processing: (ICIP’18), pp. 1393-1397, Athens, Greece, October 7–10, 2018.
  9. A. Shaffie, A. Soliman, H. Abu Khalifeh, F. Taher, M. Ghazal, N. Dunlap, A. Elmaghraby, R. Keynton and A. El-Baz, “A Novel CT-Based Descriptors for Precise Diagnosis of Pulmonary Nodules”, In: Proceedings of International Conference on Image Processing (ICIP), Taipei, Taiwan, pp. 1400-1404, 22-25 Sept. 2019.