​Dr. Hittawe's research interests are in the area of machine learning, Image processing, pattern recognition and deep learning. In the past, he has worked on Computer vision in the areas of Industrial image analysis (defects Detection and classification), Video processing (Anomalies detection in video), Bio-medical image processing (Microscopy Images), Visual servoing (Catadioptric image sequences), Signal Processing ( ECG Denoising and Waves Localization). He is currently focusing on the research of detecting and localizing extremes in the Red Sea using deep learning.

• Abnormal event detection using convolutional neural networks and 1-Class SVM classifier
  S. Bouindour, M.M. Hittawe, S. Mahfouz, H. Snoussi
  ICDP 2017
• Machine vision for timber grading singularities detection and application
  M.M. Hittawe, D. Sidibe, F. Meriaudeau
  Journal of Electronic Imaging, 2017
• Fast earth mover’s distance computation for catadioptric image sequences
  O. Tahri, M. Usman, C. Demonceaux, D. Fofi, M.M. Hittawe
  IEEE-ICIP, 2016
• Electrocardiogram signal analysing: Delineation and localization of ECG component
  O. Beya, M.M. Hittawe, K. Zegadi, E. FAUVET, O. Laligant
  BIOSIGNALS 2016
• Multiple features extraction for timber defects detection and classification with SVM
  M.M. Hittawe, S. M. Muddamsetty, D. Sidibe, F. Meriaudeau
  IEEE ICIP 2015

• ​PhD. (Artificial intelligence), University of Bourgogne, Dijon, France, 2016
• M.Sc. (Computer Science), École polytechnique, Tours, France, 2012

• ​2017-Present: Postdoctoral fellow, CEMSE, KAUST, Thuwal, Saudi Arabia

• Physical Science and Engineering Division (PSE)