Associate Professor
Department of Computer Science and Engineering
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Brief Biography

Mohamed Moustafa received his PhD in electrical engineering from the City University of New York in 2001 and has since remained active in the industry. From 1998 to 2003, he worked as a senior principal research scientist at L-1 Identity Solutions, a corporate research center in New Jersey, U.S. (now part of Morpho, France). At the center, he conducted research in specific aspects of computer vision algorithms for human facial recognition, including face detection at a distance, tracking, pose estimation and pose compensation. Since 2003, he has worked as a consultant to multinational companies including L-1 in the United States, and other companies in Germany and France, where he led multiple projects, embedded face detection into major Japanese manufacturer digital cameras, invented an efficient way to estimate the face pose angle from a face image, and built a 3D face model from a single 2D input face image.

In 2011, Moustafa joined The American university in Cairo as an associate professor with the computer science and engineering department. He is a member of the IEEE, the IEEE Computational Intelligence Society, the IEEE Technical Committee on Multimedia Computing, and the IEEE Technical Committee on Pattern Analysis and Machine Intelligence.

Moustafa holds four issued U.S. patents in the field of biometrics and computer vision. He has co-authored more than 45 research papers published in international journals and conferences. For more details, please refer to his profile at research gate


  • PhD (GPA 4/4) Electrical Engineering, The City University of New York, USA, 2001.
  • MSc Electrical and Computer Engineering, Ain Shams University, Egypt, 1997.
  • BSc Computer Engineering, with Honor degree, Ain Shams University, Egypt, 1993

Selected Publications

  • H. Adly, and M. Moustafa, “A Hybrid Deep Learning Approach for Texture Analysis,” The Second International Conference on Multimedia and Image Processing (ICMIP 2017),  Wuhan, China, March 2017.
  • Y. Abouelnaga, O. Ali, H. Rady, and M. Moustafa, “CIFAR-10: KNN-based Ensemble of Classifiers,” The 2016 International Conference on Computational Science and Computational Intelligence (CSCI'16), Las Vegas, USA, December 2016.
  • E. Ahmed and M. Moustafa, “ House price estimation from visual and textual features ,” 8th International Conference on Neural Computation Theory and Applications, NCTA'16, Porto, Portugal, November 2016.
  • H.Eraqi, Y. EmadEldin, and M. Moustafa , “Reactive Collision Avoidance using Evolutionary Neural Networks,” 8th International Conference on Evolutionary Computation Theory and Applications, ECTA'16, Porto, Portugal, November 2016.
  • M. Tolba and M. Moustafa, “GAdaBoost: Accelerating Adaboost Feature Selection with Genetic Algorithms,” 8th International Conference on Evolutionary Computation Theory and Applications, ECTA'16, Porto, Portugal, November 2016.
  • M. Raafat, B. Abdullah, M. Taher, and M. Moustafa, “Towards Privacy-Preserving Driver's Drowsiness and Distraction Detection: A Differential Privacy Approach,” International Journal of Computing and Digital Systems, vol. 5, No. 5, September 2016, pp. 365 – 374
  • M. Moustafa, “Applying deep learning to classify pornographic images and videos,” 7th Pacific Rim Symposium on Image and Video Technology (PSIVT 2015), Auckland, New Zealand, November 2015.
  • N. Shaltout, M. Moustafa, A. Rafea, A. Moustafa, and M. Elhefnawi, “Comparing PCA to information Gain as a Feature Selection Method for Influenza-A Classification,” International Conference on Intelligent Informatics and BioMedical Sciences, ICIIBMS 2015, Okinawa, Japan, November 2015.
  • Dan-Ali, A. M. and M. N. Moustafa (2014), “What is the Right Illumination Normalization for Face Recognition?”, International Journal of Advanced Research in Artificial Intelligence(IJARAI), vol. 3, pp. 24 – 28, December 2014, United Kingdom.
  • Leithy, M. Moustafa, A. Wahba, “Multi-Cascade of Complementary Features for Fast and Accurate Pedestrian Detection”, Trans. of Computer Vision and Applications, Information Processing Society of Japan, vol. 4, pp. 20 – 39, March 2012.
  • N. Houmani et al., “BioSecure Signature Evaluation Campaign: Evaluating online signature algorithms depending on the quality of signatures”, Pattern Recognition, Elsevier science, vol. 45, no. 3, pp. 993 – 1003, 2012.

Research and Teaching Interests

Moustafa's research interests include biometrics, computer vision, deep learning, machine intelligence, neural networks, genetic algorithms and embedded software development. He is currently teaching graduate courses: Neural Networks and Genetic Algorithms, Pattern Analysis, and Computer Vision, in addition to the undergraduate courses Fundamentals of Computer Vision, Practical Machine Deep Learning, and Digital Signal Processing.