Mohammed A. B. Mahmoud received the B.Sc. and M.Sc. degrees in computer
science from Department of Mathematics, Faculty of Science, Assiut
University, Assiut, Egypt, in 2007 and 2014, respectively, and his PhD degree in
School of Computer Science and Technology from the Beijing Institute of
Technology, Beijing, China in
2021. His research interests include pattern recognition, computer vision.
- TM351, TM111, TM112, T284, TM352
- Computer vision
- Machine learning
- Artificial intelligence
- (Feb. 2022 until April 2022): Assistant professor, faculty of computer science, October University for Modern Sciences & Arts - MSA University, Cairo, Egypt
- (Jan. 2021: Mar. 2021): Internship, machine learning algorithm engineer, AquaHelpers, Beijing, China
- (Sep. 2017: Nov. 2017): Internship, machine learning researcher, WellinTech, Beijing, China.
- (Feb. 2015: Aug. 2015): Assistant Lecture at faculty of computer science, Modern University for Technology and Information, Cairo, Egypt
- (Apr. 2011: Jan. 2015): Demonstrator at Thebes Academy (Higher Institute for Computer & Management Sciences), Cairo, Egypt
- (Sept. 2008: Mar.2011): Demonstrator at Giza Institute for Managerial Sciences, El-Giza, Egypt
Academic service
- A reviewer for BMVC, CVPR, ICONIP, ACCV, WACV, ICCV, ECCV and MICCAI
- A reviewer for Multimedia Tools and Applications, Computers and Electrical Engineering, Concurrency and Computation: Practice and Experience, Transactions on Intelligent Transportation Systems, IEEE Access, Transactions on Cloud
Computing and Mobile Networks and Applications journals
- Associate editor for Frontiers in Computer Science
- Mostafa, K., Hany, M., Ashraf, A., & Mahmoud, M. A. (2023, July). Deep Learning-Based Classification of Ocular Diseases Using Convolutional Neural Networks. In 2023 Intelligent Methods, Systems, and Applications (IMSA) (pp. 446-451). IEEE.
- M. A. B. Mahmoud, Arabic handwritten digit classification without gradients: Pseudoinverse Learners, In 2022 10th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC) (pp. 144-147). IEEE.
- M. A. B. Mahmoud, P. Guo, A novel method for traffic sign recognition based on dcgan and mlp with pilae algorithm, IEEE Access 7 (2019) 74602-74611.
- M. A. B. Mahmoud, P. Guo, W. Ke, Pseudoinverse Learning Autoencoder with DCGAN for Plant Diseases Classification, Multimedia Tool and Application 79 (2020): 26245–26263.
- M. A. B. Mahmoud, P. Guo, DNA Sequence Classification based on MLP with PILAE algorithm, Soft Computing 25(2020), 4003-4014.
- M. A. B. Mahmoud, P. Guo, Learning from imbalanced pulsar data by combine DCGAN and PILAE algorithm, New Astronomy 85 (2020).
- D. Xiaodan, M. A. B. Mahmoud, Y. Qian, P. Guo, An efficient and effective deep convolutional kernel-pseudoinverse learner with multi-filters, Neurocomputing, 457 (2021) 74–83.
- M. A. B. Mahmoud, P. Guo, A. Fathy, K. Li. SRCNN-PIL: Side Road Convolution Neural Network Based on Pseudoinverse Learning Algorithm, Neural Processing Letters, Accepted (2021).
- H. Abdel- Rahman, B. Mohammed. Three Strategies Tabu Search for Vehicle Routing Problem With Time Windows. Computer Science and Information Technology 2(2): 108-119, 2014.
- H. Abdel- Rahman, B. Mohammed. Applying Tabu Search in Finding an Efficient Solution for the OVRP. International Journal of Open Problems in Computer Science and Mathematics 7(4): 36-51, 2014.
Wang K, Liu P, Mahmoud MA, Guo P, Li
Y. Compute-efficient and backpropagation-free pseudoinverse learning for
neural networks: A comprehensive survey. Applied Soft Computing. 2025
Aug 29:113789.
