Khaldoun Amatoury

- Specializing in synthetic tabular and time series data generation, with a focus on advanced ML models and neural networks. - Utilizing GANs and Transformers to enhance data generation and predictive capabilities. - Applying SDV (Synthetic Data Vault) for creating secure and high-utility synthetic datasets. - Leveraging Solmetrics and SynthEval to optimize and evaluate AI model performance - Enhancing technical skills in Linux/Ubuntu, Git, Docker, and FastAPI for efficient ML model deployment.

- Developed a University Management System with Asp.net, Docker, and PostgreSQL. - Demonstrated proficiency in advanced backend technologies - Designed and implemented a Countries Project using Figma, Angular, NGRX, SCSS, and Typescript, showcasing expertise in frontend development with a focus on UI/UX principles. - Integrated Firebase Authentication and reactive forms for secure user access and dynamic user interactions.

- Worked on various CMS projects (Shopify, WordPress, Webflow). - Worked on from scratch coding website projects using the MERN stack (MongoDB, Express.js, React.js, Node.js).

- Worked with a team on developing a software platform built using the MERN stack (HTML, CSS, JavaScript, Node.js, Express.js, MongoDB, React.js). - Gained experience in agile software methodology and implemented best software development practices.

- Assisted colleagues in adding new features to the existing website. - Collaborated in developing a mobile application using Android Studio and Kotlin.

- Created python-based tools (such as web scraping using beautifulsoup, selenium, css selectors, scrapy) to fetch data from various online sources. - Parsed and stored the gathered information and data into databases. - Handled API responses and requests. - Handled big data and data frames (using pandas). - Gained knowledge in UI (Html, CSS and JS).

- Scholarship student and 4 times Dean's List recipient with a high GPA. - Accredited by the Computing Accreditation Commission of ABET.