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Research at School of Study E

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.

 

Research topic Cyber-Physical Systems

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 of Study (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:

Video: Developing a smart shirt for astronauts from Hamburg!
Wireless sensor node. Foto: Simon Ripperger
Smart Home
Research topic Data Science

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 of Study (Selection): 

  • Efficient storage,
  • communication and processing of large data volumes,
  • mathematical and algorithmic foundations of machine learning,
  • distributed data storage, distributed machine learning,
  • Machine learning for solving inverse problems,
  • Development of Data Science applications in engineering and medical technology.

► Participating institutes and cooperations: 

► The research topic is reflected in the following main research clusters:

► Interdisciplinary bundling with other topics takes place in the research fields:

► These study programs take up contents of the research topic:

 

 

Grasping Made Easy! Exhibition "Mission AI" - Deutsches Museum Bonn. Foto: Deutsches Museum/Lichtenscheidt
Research topic Energy Technology

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 of Study (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.

  • Research in electrical energy technology at TUHH focuses on overcoming central challenges that arise from this. The goal is an optimal system-technical interaction of components and technologies for the generation, transmission, storage, distribution and consumption of electrical energy. The research of future electrical energy networks of terrestrial as well as on-board energy systems plays a special role.
  • The competences of the deanery are in the field of modeling, optimization and operation management of electrical energy networks and extend in particular to the application of information and communication technology (ICT), control and automation technology as well as methods of artificial intelligence (AI).
  • The dynamics, stability and control of electrical power systems form a special focus of competence. The focus is on systems with power-electronically coupled components and increasingly sector-coupled systems with multiple energy sources.

► 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:

Integrated energy systems: planning and operation
Reliable Communications for an Inter Aircraft Network (IntAirNet)
Intelligentes Thermisches Netzwerk (iTherNet)
Stability and grid control in transmission grids with power-electronically coupled equipment
Optimal Utilization of Renewable Energies in Low Voltage Distribution Grids (OUREL)
Research topic Medical Technology

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 of Study (selection):

  • Development of medical technology systems and human-machine interfaces
  • Multi-dimensional imaging and image processing
  • Development of sensors and sensor systems
  • Modeling of electromagnetic fields in tissue
  • Safety of cyberphysical medical technology systems
  • Method development for the use of robotics and navigation in medicine

► 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.

  • Computer Science and Engineering (Informatik-Ingenieurwesen) (B.Sc./M.Sc.)
  • Electrical Engineering (Elektrotechnik) (B.Sc./M.Sc.)
  • Technomathematics (Technomathematik) (B.Sc.)
  • Computer Science (B.Sc./M.Sc.)
  • Data Science (B.Sc./M.Sc.)
  • Engineering Science (Allgemeine Ingenieurwissenschaften) (B.Sc.)
  • Biomedical Engineering (Mediziningenieurwesen) (M.Sc.)
  • Mechatronics (M.Sc.)
Collaborative robotic system to support needle placement in critical structures.
Video: Detecting epilepsy from Hamburg without contact!
Video: Developing a smart shirt for astronauts from Hamburg!
Research topic Modeling, Simulation & Optimization

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 of Study (selection):

  •     Research on numerical methods in engineering (digital twin)
  •     Approximation and optimization of complex engineering systems
  •     Formal verification of safety-critical properties of hardware and software                
  •     Modeling and simulation of communication channels and transmission of digital data
  •     Theoretical foundations of computer science and design of efficient algorithms                     
  •     Stochastic models for complex networks and random spatial structures
  •     Computer architectures for machine learning accelerators, energy-efficient GPUs

► 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.

Surface current distribution on aircraft due to High Intensity Radiated Field (HIRF) illumination.
Modeling discrete high-frequency components for high-speed communications applications.
Magnetic field distribution of a short cylindrical coil at low frequency for magnetic resonance imaging (MRI).

Institutes of School of Study E

Electrical Engineering

E-3 High-Frequency Technology
Prof. Dr. Alexander Kölpin

E-4 Communication Networks*
Prof. Dr. Andreas Timm-Giel

E-6 Electrical Power and Engineering
Prof. Dr. Christian Becker

E-7 Mikrosystems Technology
Prof. Dr. Khiem Trieu

E-8 Communications
Prof. Dr. Gerhard Bauch

E-9 Integrated Circuits
Interims Pofessor Dr. Bahr

E-12 Optical and Electronic Materials
Prof. Dr. Manfred Eich

E-14 Control Systems
Prof. Dr. H. Werner
Prof. Dr. A. Eichler

E-18 Electromagnetic Theory
Prof. Dr. Christian Schuster

 

*interdisciplinary between electrical engineering and computer science

Computer Science

Theoretical Computer Science

E-11 Algorithms and Complexity
Prof. Dr. Matthias Mnich

E-13 Algebraic Engineering
Prof. Dr. Karl-Heinz Zimmermann

E-25 Quantum Inspired and Quantum Optimization
Prof. Dr. Martin Kliesch

E-EXK6 Theoretical Computer Science
Jun.-Prof. Dr. Antoine Mottet

 

Software and Systems Engineering

E-1 Medical Technology and Intelligent Systems*
Prof. Dr. Alexander Schlaefer

E-5 Biomedical Imaging
Prof. Dr. Tobias Knopp

E-16 Software Systems
Prof. Dr. Sibylle Schupp

E-17 Telematics
Prof. Dr. Volker Turau

E-19 Data Engineering
Prof. Dr. Stefan Schulte

E-21 Data Science Foundations
Prof. Dr. Nihat Ay

E-22 Software Security
Prof. Dr. Riccardo Scandariato

 

Computer Engineering

E-4 Communication Networks*
Prof. Dr. Andreas Timm Giel

E-13 Computer Engineering
Prof. Dr. Görschwin Fey

E-13 Embedded Systems
Prof. Dr. Heiko Falk

E-15 Secure Cyber-Physical Systems
Prof. Dr. Sibylle Fröschle

E-24 Autonomous Cyber-Physical Systems
Prof. Dr. Christian Renner

E-EXK3 Smart Sensors
Jun.-Prof. Dr. Ulf Kulau

E-EXK4 Operating Systems
Jun.-Prof. Dr. Christian Dietrich

E-EXK5 Massively Parallel Systems
Jun.-Prof. Dr. Sohan Lal

 

*interdisciplinary between electrical engineering and computer science

Mathematics

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