over 22 years of experience in the software industry. My expertise lies in machine learning and deep learning algorithms. I am passionate about promoting diversity and inclusion in the workplace.

I hold an academic master’s degree in Software Engineering and Artificial Intelligence from the Egyptian E-Learning University (EELU) in Egypt.

I am currently pursuing a PhD in Software Engineering and Artificial Intelligence at Cairo University.

My thesis is titled “Enhancing Classification Performance in Heart Disease Diagnosis Using Machine Learning,” which aims to improve prediction accuracy of heart disease through the application of machine learning techniques.

I have authored and published three research papers:

1. “A hybrid GA and PSO optimized approach for heart-disease prediction based on random forest,” published by Springer on March 8, 2022.
2. “A Hybrid Bidirectional LSTM and 1D CNN for Heart Disease Prediction,” published in IJCSNS on October 21, 2021.
3. “Heart-Disease Prediction Method Using Random Forest and Genetic Algorithms,” published by IEEE on July 3, 2021.

Throughout my career, I have contributed to many projects using frameworks like TensorFlow, PyTorch, and Keras. I have actively participated in challenges such as the PyTorch Challenge, Intel OpenVINO Challenge, and AWS DeepRacer Challenge.

I have delivered several workshops on AI and data, taught at Northwestern University, and hold multiple international certifications in Big Data and Artificial Intelligence.

My expertise also includes training in software engineering and various topics within machine learning and deep learning.