Opportunities

True immersive communication requires ultra-high data rates and ultra-low latency, positioning it as a central driver in the evolution of 6G networks. The demand for low latency is fueled by the growing adoption of immersive applications across sectors such as entertainment, remote collaboration, Industry 4.0, education and training, automation, and smart cities. At the same time, the need for high data throughput stems from the use of complex media formats—such as point clouds, light fields, holography, 3D meshes, and advanced representations like radiance fields (e.g., NeRFs and Gaussian Splatting).

This research project aims to address these challenges by advancing two core areas: the efficient compression of large-scale immersive media formats and the optimized streaming of compressed content.

Recent developments in AI-based (learned) compression techniques have shown promising results and will be a central focus of this work. Once transmitted, the immersive content will be rendered on end-user devices such as VR headsets, AR glasses, or volumetric displays, and evaluated using a combination of objective and subjective metrics to assess the overall Quality of Experience (QoE).

Depending on their academic level, the candidate may:

• Apply and evaluate existing standards (e.g., codecs and streaming protocols) in novel scenarios;
• Propose innovative approaches to compression and streaming of immersive media;
• Contribute to international standardization efforts (e.g., JPEG, MPEG).