Mahamad Salah Mahmoud

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Machine Learning Research Intern
Research Institute of Sciences and Engineering• September 2021 - Present
Developing a real-time safety and awareness system using Deep Learning to detect driver drowsiness and using behavioral and vehicle measures. Designing a novel Genetic Algorithm for the optimization of Convolutional Neural Networks’ architecture, hyperparameters, and layers’ weights.
Machine Learning Research Scientist
Case Western Reserve University• October 2020 - Present
Designed and Implemented a Deep Learning architecture leveraging transfer learning and Convolutional Neural Networks for the purposes of Art Attribution using surface topography data with + 98% accuracy. Currently responsible for further developing the architecture and applying it in two art history applications: a) determining the extent of conservation in El Greco's Portrait of Cardinal Tavera; b) determining workshop contributions in El Greco's Baptism of Christ.
Machine Learning Research Assistant
Technische Universitaet Berlin• May 2020 - August 2020
Assisted in the development of a Deep Learning model [CrabNet] that uses Transformers and Self-Attention in TensorFlow and PyTorch to predict materials’ properties given only composition information. Validated, tested, and benchmarked CrabNet using the matbench task-set. Visualized the material properties results and the inner workings of the CrabNet model using UMAP and correlation matrices.