Research from the fields of electrical engineering, computer science and mathematics is united across institutes in the research topics of energy technology, cyber-physical systems, data science, medical technology and modeling, simulation & optimization.
On a higher organizational level, these research topics are reflected in various research clusters. In addition, interdisciplinary bundling with other topics takes place in the research fields of the TUHH.
Cyber-physical systems (CPS) are networked information-processing systems that interact directly with their surrounding physical environment. CPS record environmental information via sensors, process this information with computer support, and in turn influence their environment via actuators. CPS are therefore in a continuous control loop and in many application areas must perform time-critical and safety-relevant calculations and communicate with other technical systems or humans across domains.
Today, CPS are the basic technology for many "smart" products and applications worldwide. For example, they are indispensable in the fields of vehicle and aircraft construction, Industry 4.0, medical technology, automation technology, robotics and mechatronics.
TUHH's research on cyber-physical systems is characterized by the fact that it encompasses all relevant aspects - from sensors and actuators, hardware and networking, through the software of a CPS to its real applications and their certification.
► Contributions of the EIM School (selection): Secure and reliable hardware and software, novel sensor technology, networked and autonomous systems, optimization of energy efficiency and real-time capability.
► Participating institutes and collaborations:
► The research topic is reflected in the following research cluster:
► Interdisciplinary bundling with other topics takes place in the research field:
► These study programs take up contents of the research topic:
Challenge - From data to knowledge:
Smart devices are equipped with numerous sensors and produce enormous amounts of data. In practice, however, the question arises: Which data is relevant for applications such as detecting obstacles in autonomous driving or early diagnosis or prediction of diseases? Relevant data must be filtered from raw data and converted into information from which models can then be learned and knowledge built.
► Contributions of EIM School (Selection):
► Participating institutes and cooperations:
► The research topic is reflected in the following main researchclusters:
► Interdisciplinary bundling with other topics takes place in the research fields:
► These study programs take up contents of the research topic:
A world without electrical energy is unthinkable today, and global electricity generation is constantly increasing. At the same time, new challenges are arising from the envisaged energy turnaround. The phase-out of nuclear energy and coal-fired power generation is drawing ever closer. Wind power and photovoltaic plants are now a natural part of our landscape. In this context, the use of hydrogen to generate energy has been the subject of particularly intensive research for some time. A prerequisite for a positive contribution to climate protection is the production of hydrogen from renewable energy sources.
Consequently, the energy systems of the modern world must be profoundly transformed.
► Comtributions of the EIM School(sleection): Intelligent electrical energy networks (smart grids), Integration of power-electronically coupled systems, Efficient on-board energy systems for modern aircraft and ships, Operation and planning for integrated/sector-coupled energy systems.
► Participating institutes and collaborations:
► The research topic is reflected in the following research clusters:
► Interdisciplinary bundling with other topics takes place in the research fields:
► These study programs take up contents of the research topic:
Modern patient care has already been decisively improved by the continuous development of medical technology. Diseases can now be detected at an early stage and treated more effectively.
Future improvements require the fusion of various disciplines from computer science, engineering, mathematics and medicine. Here, the combination of modern imaging methods and sensor technologies with methods for image processing and machine learning as well as the methods for planning and support in treatment processes are crucial building blocks.
► Contributions of the EIM School (selection):
► Participating institutes and collaborations:
► The research topic is reflected in the following research cluster:
► Interdisciplinary bundling with other topics is carried out in the research field:
► These study programs at the TUHH take up contents of this research topic.
Many scientific and engineering objects/processes can be described approximately by mathematical models. Based on theoretical analyses and efficient numerical solutions of these usually very complex models, the processes of the real world can then be digitally simulated and thus better understood and, if necessary, optimized (e.g. with regard to performance, energy efficiency, safety).
► Contributions of the EIM School (selection):
► Participating institutes and collaborations:
► The research topic is reflected in the following research clusters:
► Interdisciplinary bundling with other topics is carried out in the research field:
► All courses of study at the TUHH take up contents of this research topic.
E-3 High-Frequency Technology
Prof. Dr.-Ing. Alexander Kölpin
E-4 Communication Networks*
Prof. Dr.-Ing. Andreas Timm-Giel
E-6 Electrical Power and Energy Technology
Prof. Dr.-Ing. Christian Becker
Prof. Dr.-Ing. Roland Harig (Honorary Professor)
E-7 Mikrosystems Technology
Prof. Dr.-Ing. Khiem Trieu
E-8 Communications
Prof. Dr.-Ing. Gerhard Bauch
E-9 Integrated Circuits and Systems
Prof. Dr. Qiang Li
E-12 Optical and Electronic Materials
Prof. Dr. Manfred Eich
Prof. Dr. Alexander Petrov (Honorary Professor)
E-14 Control Systems
Prof. Dr.-Ing. Timm Faulwasser
Prof. Dr.-Ing. Annika Eichler
E-18 Electromagnetic Theory
Prof. Dr. sc. techn. Christian Schuster
E-23 Power Electronic Devices
Prof. Dr.-Ing. Holger Kapels
*interdisciplinary between electrical engineering and computer science
E-11 Algorithms and Complexity
Prof. Dr. Matthias Mnich
E-25 Quantum Inspired and Quantum Optimization
Prof. Dr. Martin Kliesch
E-EXK6 Theoretical Computer Science
Jun.-Prof. Dr. Antoine Wiehe (née Mottet)
E-1 Medical Technology and Intelligent Systems*
Prof. Dr.-Ing. Alexander Schlaefer
E-5 Biomedical Imaging
Prof. Dr.-Ing. Tobias Knopp
E-16 Software Systems
Prof. Dr. Sibylle Schupp
E-19 Data Engineering
Prof. Dr.-Ing. Stefan Schulte
E-21 Data Science Foundations
Prof. Dr. Nihat Ay
E-22 Software Security
Prof. Dr. Riccardo Scandariato
E-EXK7 Human-Centric Machine Learning
Jun.- Prof. Dr. Pierre-Alexandre Murena
E-4 Communication Networks*
Prof. Dr.-Ing. Andreas Timm Giel
E-13 Computer Engineering
Prof. Dr.-Ing. Görschwin Fey
E-13 Embedded Systems
Prof. Dr. Heiko Falk
E-15 Secure Cyber-Physical Systems
Prof. Dr. Sibylle Fröschle
E-17 Networked Cyber-Physical Systems
Prof. Dr. Olaf Landsiedel
E-24 Autonomous Cyber-Physical Systems
Prof. Dr.-Ing. Christian Renner
E-EXK3 Smart Sensors
Jun.-Prof. Dr.-Ing. Ulf Kulau
E-EXK5 Massively Parallel Systems
Jun.-Prof. Dr.-Ing. Sohan Lal
*interdisciplinary between electrical engineering and computer science
E-10 Applied Analysis
Prof. Dr. Marko Lindner
E-10 Computational Mathematics
Prof. Dr. Daniel Ruprecht
E-10 Discrete Mathematics
Prof. Dr. Anusch Taraz
E-10 Numericale Mathematics
Prof. Dr. Sabine Le Borne
E-10 Stochastics
Prof. Dr. Matthias Schulte
E-EXK8 Ethics in Technology
Jun.-Prof. Dr. Maximilian Kiener
E-26 Engineering Education Research
Prof. Dr. Christian Kautz