Hamdi Abed

Bis 2018, Mechatronics, Systems Engineering, University of Debrecen

Über mich

I am passionate Machine Learning/ Deep Learning engineer. a goal-driven individual who is keen to expand my professional talents, with a primary concentration on exploring State-of-Art Deep Learning algorithms and optimizing Deep Neural Network structures.

Fähigkeiten und Kenntnisse

Machine Learning
Deep learning
Artificial intelligence
Attention
Data Science
Python
Computer Vision
Natural Language Processing
PyTorch
TensorFlow
wandb
Docker
Linux
AWS
NumPy
pandas
matplotlib
lstm
Fitness
Efficiency

Werdegang

Berufserfahrung von Hamdi Abed

  • 7 Monate, Juni 2019 - Dez. 2019

    Machine Learning Engineer

    Continental AG

    Researched the efficiency and scalability of existing reinforcement learning-based AutoML. Focused on finding an optimal CNN solution via ENAS and DARTs search algorithms to fit in a limited memory microcontrollers. ENAS model was implemented using Python-based ML framework TensorFlow. Dataset was handled using Sci-Kit Learn, Numpy, Pandas, and MatPlotLib. Evaluation logs were monitored using TensorBoard and WandB technologies. Models were containerized using Docker and trained on GPUs within Linux OS.

Ausbildung von Hamdi Abed

  • Bis heute 5 Jahre und 10 Monate, seit Sep. 2018

    Machine Learning Engineering

    Budapest University of Technology and Economics

    Was awarded the Stipendium Hungaricum full-funded scholarship program to complete Ph.D. studies. • Proposed Ph.D. topic: "Optimization of Automated Machine Learning models". • Develop deep neural networks structures and applications in various set of tasks. • Implement efficient deep learning models in Natural Language Processing (NLP) and sequential data modelling. • The research focuses on state-of-art models such as: Transformers, LSTM, RNN, CNN, and TCN.

  • 2 Jahre und 6 Monate, Feb. 2016 - Juli 2018

    Mechatronics, Systems Engineering

    University of Debrecen

    Awarded the Stipendium Hungaricum full-funded scholarship program to complete MSc studies. • GPA: 4.88/5.0 • Studied Mechatronics and robotics systems, signal processing, and sensory systems. • Applications of electrical and electronics techniques, using LabView to create Mechatronics systems, and Control and supervisory systems design. • Graduation thesis topic for MSc: "LabView-based Cars detection using Machine Learning approaches".

  • 4 Jahre und 5 Monate, Sep. 2009 - Jan. 2014

    Electrical Engineering

    Islamic University of Gaza

    A BSc in Electrical Engineering studies, including signal processing, digital signal processing, telecommunications, control systems, intelligent data analysis, digital design, electrical and electronic devices, probability theory, and statistcs.

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