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Research at School of EIM

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
Jun.-Prof. Ulf Kulau
Video: Developing a smart shirt for astronauts from Hamburg!

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:

Research topic Data Science
Grasping Made Easy! Exhibition "Mission AI" - Deutsches Museum Bonn.

Foto: Deutsches Museum/Lichtenscheidt

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): 

  • 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 researchclusters:

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

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

 

 

Research topic Energy Technology
Integrated energy systems: planning and operation

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.

  • 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:

Research topic Medical Technology
Collaborative robotic system to support needle placement in critical structures.
Collaborative robotic system to support needle placement in critical structures.

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):

  • 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.)
Research topic Modeling, Simulation & Optimization
Modeling-Simulation-SHIP
Generated with the CONCEPT-II advanced electromagnetic field simulator for the numerical computation of radiation and scattering problems in the frequency domain developed by the Institute of Electromagnetic Theory. https://www.tet.tuhh.de/en/concept-2/

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):

  •     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.

Institutes of School of Electrical Engineering, Computer Science and Mathematics

Electrical Engineering

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

Computer Science
Letters NCPS in blue

Theoretical 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)

 

Software and Systems Engineering

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

Computer Engineering

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

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

 

Ethics in Technology

E-EXK8 Ethics in Technology
Jun.-Prof. Dr. Maximilian Kiener

 

Education Research

E-26 Engineering Education Research
Prof. Dr. Christian Kautz

 

Video

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