Media Informatics studies the new software architectures, algorithms and data structures, tools, and user interfaces required and enabled by the use of multiple media, in particular time-based media such as audio and video, in computer systems and applications.
Within Media Informatics, Human-Computer Interaction (HCI) may harbor one of the biggest upcoming challenges: Inventing and studying new and appropriate user interface devices, techniques, and metaphors for the deployment of new technologies in a world beyond the single-user desktop. Another current key challenge in HCI is the successful collaborative use of interactive systems. People still use email for collaboration because more advanced tools are not interoperational, multipoint- and team-centered yet, or assume very structured, static work environments. Integrated Collaborative Environments (CEs) are the solutionbut they pose challenging research questions.
Research Area 2: Communication Systems Engineering
Communication networks, in particular mobile communication and the Internet, have revolutionized our daily life and business. New ways of exchanging data through different types of networks are continuously evolving.
Our research will concentrate on three vertical areas: New Network Architectures (Designing the future global network), Self-organizing Systems (Engineering the Foundations of Autonomous Networks), and Middleware and New Services (Scalable Bridging in todays Networks). These activities are complemented by the horizontal area New Methods and Tools for Performance Evaluation. Moreover, real-world applications (e.g., from mobile commerce or transport telematics) will be deployed to verify the research work.
Research Area 3: Software and Information Engineering
New challenges and opportunities of Information System Engineering arise in connection with the immense expansion of semi-structured data, text and images through the growth of the Internet, and the fast evolution of services that become available on a global scale.
From the Software Engineering perspective, these developments exploit the methodologies and emerging standards of object-oriented paradigms, models, and languages, service and model-driven architectures, aspect-oriented and agile programming.
Process Management, considered a core domain of software engineering and business informatics research, is less well-structured than traditional applications, requiring new media and interaction metaphors to ensure usability.
Life Science Informatics as a research field is best rationalized as the unification of classical bioinformatics, chemoinformatics, and medical informatics. This reflects the complexity and strong interdisciplinary character of modern research and development in the Life Science arena and the strong interplay between theoretical and experimental concepts. Current major research topics world-wide concern the integration of genomic models and algorithms, structural models and chemical properties, cellular function and biological network models into a system-oriented view.
Within these fields special approaches to data analysis and data mining as well as bio-ontologies and data models are used.
Synthesizing images and animations from abstract scene descriptions still constitutes the very core of Computer Graphics, but recent developments have enlarged the target range of the synthesis from purely visual output to multiple modes including sound, haptic feedback, or even smell. At the same time the underlying scene descriptions are extended to include the necessary information to render all these modes and the level of detail in such descriptions has increased drastically. For example current 3D model descriptions may span several geometric scales from large geometric structures to microscopic material properties. As a consequence, new algorithms have to be developed for the generation, modification, and display of complex 3D models. The cost-efficient availability and increasing quality of these datasets open the way to new exciting applications. Especially in the context of mobile multimedia application scenarios and in numerical simulations, the algorithmic requirements in terms of efficiency, flexibility, and robustness are very high. Within just a few years, e.g., the computer games market has grown beyond traditional entertainment industries such as movie production and in the industrial production process, Virtual Reality applications and Computational Engineering have mostly replaced the building of real prototypes.
For centuries, secure communications were mainly the domain of secret services, diplomats, and the military but today cryptography and secure communications are enabling technologies without which activities like electronic commerce cannot flourish.
The current challenges are manifold. On the practical side, more powerful cryptography has to function on less powerful devices, such as mobile implements, in ad-hoc or peer-to-peer networks, on smart cards or RFIDs. On the theoretical side, the current requirement for cryptographic proposals is that they come with a security reduction, showing that a break of the system implies the efficient solution of a standard computational problem that is not supposed to have one. The tasks here include general constructions that put several secure components together and still are secure, and applications of this technology in areas such as biometry and steganography. Elliptic curves have emerged as a central tool in modern cryptography. Their practical applications, including pairings for identity-based encryption, are still amenable to many improvements.
Research Area 7: Data Mining, Pattern Recognition and Learning
Data mining, pattern recognition and learning are subfields of computer science concerned with algorithms and systems for the computer assisted analysis of large data sets, with the goal of uncovering hidden patterns or knowledge useful for classification, prediction and decision making, and with algorithms capable of processing input data with the goal of making a system adaptive to its environment and/or task.
For classical business data, the wide-spread use of electronic commerce and the arrival of new technologies like RFID tagging are causing an exploding amount of data, but also newer data types like text, speech, images and other multimedia material are creating large amounts of data for pattern recognition and data mining. From environmental surveillance to security applications, sensor networks and video tracking are becoming more and more important, and we are seeing the first autonomous devices being deployed that need data analysis and learning techniques to adapt to their environments.
Research Area 8: Algorithm Design and Formal Foundations of Applied IT
This research area is concerned with fundamental problems, methodologies and paradigms occurring in most of the other research areas of the B-IT Research School. The focus of this area will be on the following topics and various interactions between them:
Design and analysis of efficient algorithms, with the central objective of surmounting the barriers of intractability that are present in handling massive data or data distributed networks.
Development of adequate formal models of complex systems in order to support automated design and analysis, where complexity refers to different dimensions (not only system size, but -- also, for example -- its structural aspects like parallelism and the necessity to integrate different types of data).
(Bold letters indicate the professors currently in charge of the respective research area.)