Application Areas

• Interoperable & Adaptive Educational Infrastructures
• State of the Art Media Delivery for Cross Device Applications
• Secure Verifiability of Media Production, Modification and Usage Processes

Research Areas

• Artificial Intelligence & Machine Learning for Media
• Personalization & Support through Adaptive Systems & Recommender Systems
• Data Analysis through Pattern Recognition & Predictive Data Mining
• Supervised, Unsupervised & Reinforcement Learning Approaches based on Deep Learning
• Sustainable Interoperable Infrastructures
• Design of Micro-Service Architectures to support the Best-of-Breed Paradigm
• Analysis and Support of Open Standards & Specifications
• Translation of Business Requirements into Scientific Technical Solutions
• Technical Innovations for Societal Challenges
• Secure Verification of Authenticity and Provenance for Media and Physical Objects
• Broad Acceptance through Explainable AI & Trustworthy AI
• User Self-Sovereign Identities and Data Handling

Dr.-Ing. Christopher Krauss is Media & Data Science Lead at the business unit Future Applications and Media of the Fraunhofer Institute for Open Communication Systems (FOKUS). He specializes in the R&D of topics dealing with Machine Learning, Data Science, Technology Enhanced Learning, and Connected TVs and has been involved in multiple public founded national and international projects (e.g. Smart Learning I & II, Digi-Hand, FI-Content I & II, User Centric Networking, Global ITV) and managed many projects for different industry customers (e.g., Red Bull, Deutsche Welle, MediaBroadcast, ImmobilienScout24, Holtzbrinck Publishing Group, Cornelsen, Bertelsmann Arvato, Axel Springer, Rovi, and Deutsche Telekom).

Christopher Krauss received his Master of Science in Media Informatics (very good with distinction) at Beuth University of Applied Sciences and Fraunhofer FOKUS in 2012. From 2015 until 2017, he participated in the BMBF-funded Software Campus program which trains and professionally develops tomorrow’s senior IT executives. In June 2018, Christopher Krauss completed his PhD project (with distinction/ summa cum laude) at the TU Berlin with his dissertation “Time-Dependent Recommender Systems for the Prediction of Appropriate Learning Objects”.