Working Areas:

• Deep learning and machine learning applications in media compression and streaming
• Full-stack development with a focus on learning technologies
• Environmental sustainability in digital media through green streaming initiatives
• Application of machine learning and deep learning in health technology, specifically in movement disorders

Curriculum Vitae

After completing his bachelor's degree in Computer Science in Tunisia, Ahmed Amine Mchayaa moved to Germany to pursue a master's degree in Computer Science, specializing in Data and Software Engineering. His career then took a pivotal turn toward full-stack development within the field of learning technology, where he nurtured a growing passion for video, streaming, and all things related to digital media. This enthusiasm led him to join the Future Applications and Media (FAME) division at the Fraunhofer FOKUS, where he focused on the Deep Encode project. The project's aim is to significantly reduce bitrate and video size while maintaining high quality, which is perfectly in line with his interests and skills.

His master's thesis, titled “Detection of Freezing of Gait Episodes in Parkinson’s Patients Based on Inertial Data from Wrist Sensor,” completed in August 2023, marked a significant milestone in Ahmed Amine Mchayaa's career. It deepened his understanding of machine learning and deep learning, knowledge he immediately applied to enhance the Deep Encode project's objectives of generalizing the solution for various types of video.

In September 2023, he transitioned from being a student to a full-time employee at FAME. His current focus is on integrating the Deep Encode solution into green streaming initiatives, aiming to minimize the CO2 footprint emitted of streaming content online. His journey from a Computer Science student in Tunisia to a key player in Germany's technology industry reflects his dedication to combining technological innovation with environmental sustainability.