Lukas Famula

The project aims to develop a specialised AI-powered system that enables the automatic generation of audio files from article texts. The implementation of advanced deep learning algorithms tailored to the challenges of natural speech synthesis ensures high quality and naturalness in audio generation. My role is to implement this AI system to enable editorial teams and content creators to efficiently produce and distribute their content in audio format.

The project to redesign Geschenkzeitung.de involved the development of a modern website with a fresh logo and an improved user experience. As part of the development team, my role was to connect external interfaces to ensure the integration of services and features. By implementing these interfaces, a seamless connection between the website and external services was created, which helped Geschenkzeitung.de to provide an improved service to its customers.

On this project for the heavy metal band Rigorious, I was responsible for connecting to the headless CMS Sanity.io, creating the data models for the content structure, and connecting to external data sources such as Bandsintown and Spotify.
I also acted as an interface between the band and the design team to ensure that the band's wishes and requirements were met.

As part of the project to develop an advanced AI system for the automatic detection and classification of hazards in fluoroscopy facilities, I was responsible at various levels. I led the project planning and control and monitored the progress of the implementation of image data pre-processing techniques to create an optimal basis for AI analysis. In addition, I planned and realised the data acquisition and designed customised AI models tailored to the specific requirements of the plants. Furthermore, I conducted the training and validation of the AI models and designed and built embedded hardware architectures to efficiently integrate the AI algorithms. Finally, I implemented the user interface to enable user-friendly interaction with the system.

Working closely with customers in the automotive industry, we developed custom AI systems for predictive maintenance of casting processes. My role involved pre-processing and analysing image data to enable accurate predictions and to ensure that the AI models were trained with high quality data. I was also responsible for the implementation and run-time optimisation of the AI systems, with a particular focus on efficiency to ensure seamless integration into our customers' production processes.

As part of a project to develop state-of-the-art microarchitecture applications in the context of a merchandise management system, my focus was on implementing an anti-corruption layer as an interface between the individual systems. This layer ensured secure and reliable data transfer, regardless of the different data formats and protocols of the various systems. I was also responsible for the connection to an SAP system using a REST API to enable smooth communication and data transfer. These measures maximised the flexibility, scalability and efficiency of the overall system and ensured seamless integration into existing SAP systems.