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I am Mohamed Saber, a passionate Computer Engineering graduate with hands-on experience in machine learning, software development, and data analysis. I enjoy building innovative AI solutions, such as cry detection systems for infants and interactive pose estimation applications. I thrive in collaborative environments and have demonstrated my skills through internships and competitions. With a strong foundation in algorithms, AI, and software foundations, I have applied my knowledge through real-world projects and internships at companies like Neolook Solutions and CAPPELLA. I am eager to continue advancing my expertise and contribute to impactful technological developments in AI and software engineering.…I am Mohamed Saber, a passionate Computer Engineering graduate with hands-on experience in machine learning, software development, and data analysis. I enjoy building innovative AI solutions, such as cry detection systems for infants and interactive pose estimation applications. I thrive in collaborative environments and have demonstrated my skills through internships and competitions. With a strong foundation in algorithms, AI, and software foundations, I have applied my knowledge through real-world projects and internships at companies like Neolook Solutions and CAPPELLA. I am eager to continue advancing my expertise and contribute to impactful technological developments in AI and software engineering.

Mohamed Saber

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I am Mohamed Saber, a passionate Computer Engineering graduate with hands-on experience in machine learning, software development, and data analysis. I enjoy building innovative AI solutions, such as cry detection systems for infants and interactive pose estimation applications. I thrive in collaborative environments and have demonstrated my skills through internships and competitions. With a strong foundation in algorithms, AI, and software foundations, I have applied my knowledge through real-world projects and internships at companies like Neolook Solutions and CAPPELLA. I am eager to continue advancing my expertise and contribute to impactful technological developments in AI and software engineering.…I am Mohamed Saber, a passionate Computer Engineering graduate with hands-on experience in machine learning, software development, and data analysis. I enjoy building innovative AI solutions, such as cry detection systems for infants and interactive pose estimation applications. I thrive in collaborative environments and have demonstrated my skills through internships and competitions. With a strong foundation in algorithms, AI, and software foundations, I have applied my knowledge through real-world projects and internships at companies like Neolook Solutions and CAPPELLA. I am eager to continue advancing my expertise and contribute to impactful technological developments in AI and software engineering.

Available to hire

I am Mohamed Saber, a passionate Computer Engineering graduate with hands-on experience in machine learning, software development, and data analysis. I enjoy building innovative AI solutions, such as cry detection systems for infants and interactive pose estimation applications. I thrive in collaborative environments and have demonstrated my skills through internships and competitions.

With a strong foundation in algorithms, AI, and software foundations, I have applied my knowledge through real-world projects and internships at companies like Neolook Solutions and CAPPELLA. I am eager to continue advancing my expertise and contribute to impactful technological developments in AI and software engineering.

Skills

Experience Level

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Work Experience

Machine Learning Engineer at Neolook Solutions

May 31, 2025 - August 22, 2025

Developed a joint angle analysis system for infant movement videos by extracting keypoints and calculating angles using vector mathematics. Built a Dash-based web app to visualize real-time pose estimation and symmetry analysis integrating video playback and graphs. Trained a cry detection model using Amazon SageMaker Estimator, improving training time significantly and implemented a Sparse Transition Variational Autoencoder (ST-VAE) with PyTorch to enhance detection accuracy. Used Kullback-Leibler divergence for audio classification and utilized Prometheus and Grafana for monitoring user access in a Django-based baby inspection service.

Machine Learning Intern at CAPPELLA

September 30, 2024 - August 22, 2025

Conducted a literature review on AI and deep learning methods for baby cry detection. Preprocessed and analyzed audio data using Python libraries. Automated audio dataset downloading and extraction. Designed and trained a CNN-LSTM model using PyTorch for audio classification, labeling baby cry durations to select clean audio samples. Converted audio to mel-spectrograms and monitored model training using early stopping to optimize accuracy and prevent overfitting.

IT Department Intern at ADNOC Offshore

August 31, 2023 - August 22, 2025

Applied data transformation on files using Power BI for data visualization. Created policies on Fortinet Firewall to monitor LAN traffic. Replaced HDDs of company laptops with SSDs and installed corporate software via BIOS.