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Try to search the institute's name on your favorite search engine for more details about the institute.

About the Institute

Institute of Communication Networks has 3 main research areas:



1. Mobile and Space communication (focus on shipping, aviation, vehicular and space applications, modelling of delay, reliability and availability)
   
2. Future Internet and Network Planning (virtualization, optimization of SDNs, performance optimization with Machine Learning)
   
3. Sensor Networks, IoT and opportunistic networks (realization and modeling of reliable communication networks for safety critical applications, performance optimization)



More details on our current ongoing BMBF/DFG/EU funded research projects can be found at https://www.tuhh.de/et6/research/projects



Please also refer to our completed list of Student Theses to get an overview about the topics we have offered so far: https://www.tuhh.de/et6/student-theses/completed-master-theses-and-diplomarbeiten.



Contact Person

Contact person's name - Koojana Kuladinithi

Contact person's email address - comnets@tuhh.de

Contact person's phone number (if applicable) – 3533

Website

https://www.tuhh.de/et6/research/projects 

About the Institue

The Institute for Biomedical Imaging (IBI) was founded in 2014 by Tobias Knopp and is a joint research department of the University Medical Center Hamburg-Eppendorf (UKE) and the Hamburg University of Technology (TUHH). Medical imaging is the non-invasive imaging of sections of the human body and plays an important role in the diagnosis, treatment and post-treatment of diseases. Effective, safe and high quality imaging is essential for many medical decisions and can prevent unnecessary medical procedures. Our research interests lie in the field of tomographic imaging, with a focus on Magnetic Resonance Imaging (MRI) and the young imaging technique Magnetic Particle Imaging (MPI).  In particular, we are working on the hardware development of MPI systems, the research of new signal processing, image reconstruction and image processing algorithms, and the evaluation of medical applicability. In close cooperation with our clinical partners at the UKE, we also conduct translational research with the goal of bringing state-of-the-art acquisition and reconstruction methods into clinical routine.

Keywords

Medical Imaging, Signal Processing, Machine Learning, Magnetic Particle Imaging, Magnetic Resonance Imaging

Contact person

Martin Möddel

Website

 https://www.tuhh.de/ibi/thesis

more info https://www.tuhh.de/ieet/en/home

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About the Institute

Research at the Institute of Communications deals with various technical aspects of wireless and wired systems for communication, localization, and sensing. Exemplary applications span terrestrial cellular networks, aeronautical systems (air-to-ground and in-cabin), satellite transmission, as well as acoustic communication/localization under water, and fiber-optical transmission.

The investigated concepts focus on the physical and medium access control layer of the protocol stack. For that purpose, methods of digital signal processing and error control coding with coarsely quantized data are developed, based on applied information theory. Moreover, energy- and bandwidth-efficient transmission schemes are designed using principles from machine learning. Other aspects include cooperative localization, joint communication and sensing (JCAS), and interference management in cellular networks, e.g. applying multiple antennas (MIMO).

Our research topics are available from our website (https://www.tuhh.de/nt/en/home) or from the info screen in building N (second floor, Z2). Please contact the relevant research assistants directly for possible open projects.

Keywords

Mobile communication, cellular networks, aeronautical systems, localization, joint communication and sensing, satellite communication, underwater communication and localization, interference management, MIMO, error control coding, digital transmission schemes

Contact Person

Frau Andrea Dageförde and Frau Irma Schuster, E-Mail: sek.nt@tuhh.de.

Website

https://www.tuhh.de/nt/en/home

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E-10 consist of 5 institutes:

• E-10 Applied Analysis Prof. Dr. Marko Lindner
• E-10 Computational Mathematics Prof. Dr. Daniel Ruprecht
• E-10 Discrete Mathematiics Prof. Dr. Anusch Taraz
• E-10 Numericale Mathematics Prof. Dr. Sabine Le Borne
• E-10 Stochastics Prof. Dr. Matthias Schulte

The Mathematics Department covers the fields Applied Analysis, Discrete Mathematics, Computational Mathematics, Numerical Mathematics and Stochastics. A Bachelor or Master thesis typically builds upon a special topic course. If you are interested, please approach the lecturer directly at the end of the course to inquire about potential thesis topics.

more info https://www.tuhh.de/algo/theses

More info about the institute on their webpage: https://www.tuhh.de/oem/en/institut/institut

E-13 is shared between two insitutes:

• E-13 Computer Engineering Prof. Dr. Görschwin Fey
• E-13 Embedded Systems Prof. Dr. Heiko Falk

More info about thesis requests are found on the institute's website https://www.tuhh.de/es/theses

Try to search the institute's name on your favorite search engine for more details about the institute.

Try to search the institute's name on your favorite search engine for more details about the institute.

More info available on the following websites:

• https://www.tuhh.de/sts/lectures/thesis-projects
• https://www.tuhh.de/sts/lectures/faq-thesis-projects

Contact Person

Prof.Dr.sc.techn. Christian Schuster

Head of Institute

Phone: 040 42878-3116
schuster@tuhh.de

Room: 2.007

Website

1. https://www.tet.tuhh.de/
2. https://www.tet.tuhh.de/en/institute/
3. https://www.tet.tuhh.de/forschung/
4. https://www.tet.tuhh.de/en/research/

About the Insititue

The Institute for Data Engineering strives to provide the means to process (big) data from, within, and beyond the Internet of Things (IoT). For this, we investigate and apply methods and mechanisms from the fields of data engineering and elastic computing. The proliferation of these technologies enables both small-scale and large-scale smart environments and systems for smart cities, smart energy grids, and smart factories. A special focus is on Quality of Service (QoS) and Quality of Experience (QoE) aspects. 

An important focus of our research are blockchain technologies, both with regard to the application of blockchains in novel areas (especially the Internet of Things) and fundamental research (especially with regard to blockchain interoperability). Recently, a primary research focus is also federated learning, i.e., distributed machine learning which leads to benefits regarding data protection and communication overhead. 

Finally, we work at the interface between distributed computing and theory where we analyze systems, models, and algorithms from both an empirical and a theoretical point of view.

Keywords

Data Engineering, Federated Learning, Blockchain, Internet of Things, Distributed Computing

Contact person

Dr. Dominik Schallmoser
dominik.schallmoser@tuhh.de
+49-40-42878 2524

Website

https://www.tuhh.de/ide/homepage

Institute for Data Science Foundations (E-21)
Hamburg University of Technology  TUHH
Hamburg Innovation Port HIP ONE

Blohmstraße 15 (5th floor)
21079 Hamburg

Contact Person

Imke Bartscher & Daniela Gascon Bosqued
Assistants to Prof. Dr. Nihat Ay

phone: +49 40 428 78 49 32
e-mail: dsf-office@tuhh.de

About the institute

The overall mission of the institute is to build round-trip security & privacy engineering methods, which are based on lightweight design models and connect the design models with the implementation code, in the context of fast-paced, continuous, and decentralized development ecosystems. In this research agenda, an important role is played by the use of ML/AI, as well as the adoption of other emerging trends, like dev-bots, i.e., security-oriented intelligent agents that seamlessly collaborate with human developers.

Keywords

Our research covers a wide range of activities related to the design and implementation of secure and privacy-friendly applications, particularly in the realms of micro-services, IoT ecosystems, and cyber-physical systems.

Contact Person

To join a theses at our institute please check the website 
Requests email: e-22-arbeit@tuhh.de 

Website

https://www.tuhh.de/softsec/teaching/thesis

Contact Info

Tel.   +49 40 42878-4800
Email: acps-sekretariat@tuhh.de
Room:  HS28 1.022

Website

https://www.tuhh.de/acps/welcome

About the Institute

The research at the institute is addressed at topics from quantum and quantum-inspired computing. Theses topics on quantum computing usually require prior knowledge on quantum mechanics (such as projective measurements) whereas quantum-inspired computing requires only standard computer science skills.

Keywords


Quantum computing, quantum inspired computing, physics inspired algorithms, combinatorial optimization, quantum algorithms, readout of quantum computers, applied mathematics

Contact person

Martin Kliesch, martin.kliesch@tuhh.de

Website

See www.tuhh.de/quantum for more information on our institute and https://www.tuhh.de/quantum/study/master-and-bachelor-theses-topics on information on theses topics and supervision.

About the Institute

The Engineering Education Research Group at Hamburg University of Technology (TUHH) investigates teaching and learning processes in engineering. A special focus is on analyzing student understanding of key concepts and their relationships in basic engineering courses such as Fundamentals of Electrical Engineering, Engineering Mechanics, Differential Equations, Programming and Computer Science, and Fluid Dynamics.

In our research, we use qualitative as well as quantitative empirical methods, e.g. semi-structured interviews and diagnostic tests. Through our close collaboration with the Zentrum für Lehre und Lernen (Center for Teaching and Learning), the results of this research can be immediately applied in the teaching at TUHH.

Keywords

Engineering education; conceptual understanding; active-learning methods; misconceptions; concept inventories.

Contact

Prof. Dr. Christian H. Kautz
Email: kautz@tuhh.de
Phone: -4259

Website

http://www.tuhh.de/fachdidaktik

About the Insitute

Our research focus is digital data and signal processing, real-time data processing, energy-efficient processing, as well as reliability, fault tolerance and embedded fault diagnosis in the context of 'smart' sensor technology and resource constrained devices. In addition, many of our projects are assigned to the field of space applications, in which the challenging environmental conditions in the above-mentioned research are addressed in particular.

Keywords

Ressource contained Sensor Systems
Embedded Signal Processing (MCU, DSP, FPGA)
Fault-Tolerance and Reliable Computing
Low-Power Processing
Space Applications and Electronics

Website

link to a webpage of institute's website where this info is available:

https://www3.tuhh.de/e-exk3/People/kulau/

https://www3.tuhh.de/e-exk3/kontakt.html

About the Insittute

The Massively Parallel Systems Group (MPS) is dedicated to researching and teaching computer architecture, with a specific focus on massively parallel systems. These days massively parallel systems are present everywhere – in our smartphones to supercomputers. They help us to do many things which were not possible before. For example, the recent stupendous success of machine learning, especially deep learning, is mainly due to the exponential increase in computational power. As such, machine learning is not new. Machine learning methods are around since the 1950s. What has predominately changed now is the computing power, with many-core processors such as GPUs as the main drivers. If these massively parallel processors are not utilized properly, they are very expensive in terms of power and energy consumption, which is not good as we aspire to reduce our carbon footprint. At MPS, we are developing new hardware/software techniques to make computing devices more performance and energy-efficient while also improving their programmability.

Keywords

1. Computer architecture/GPU architecture
2. Machine learning for computer architecture
3. Power and performance modeling
4. Memory system, memory compression, approximate computing
5. Heterogeneous computing (porting/optimizing applications)
6. Runtime support for HPC systems
7. Harnessing AI for post-silicon validation
8. Embedded GPUs for space and automotive systems

Contact Person

Name: Mr. Tim Lühnen
Email address: tim.luehnen@tuhh.de
Phone number (if applicable): +49 40 42878 6101

Website

Information about our group's research activities and open theses is also available at:
https://www.mps.tuhh.de/research/
https://www.mps.tuhh.de/theses/

About the Institute

The research group for theoretical computer science is specialised in the study of computational problems from the point of view of mathematics. We aim at understanding the complexity of solving particular tasks and in particular we aim at understanding why some tasks are computationally easy (say, solving a system of linear equations) and why some tasks are computationally hard (for example, solving a Sudoku grid). At the heart of our research is the famed P vs. NP problem (https://en.wikipedia.org/wiki/P_versus_NP_problem), one of the most famous open problems in mathematics and computer science. The tools that we use in our research are diverse and originate in fields of mathematics such as algebra, topology, combinatorics, or model theory.

Keywords

Constraint satisfaction problems, computational complexity, algebra

Contact Person

Prof. Dr. Antoine Mottet
Email: antoine.mottet@tuhh.de
Phone: -2859

Website

Website: tuhh.de/tcs

About the Institute

The research group on human-centric machine learning focuses on the question of making humans and AI collaborate in efficient ways in various tasks, such as language learning, creativity, problem solving or even machine learning or statistical modelling. Among all possible interactions between a human and an AI agent, we study the specific problem where the AI agent plays the role of an assistant, providing advice and directions to the human. To do so, this artificial agent needs to understand the motivations and preferences of the human, in order to anticipate their potential mistakes and their reactions in general. This is challenging, becauses such predictions must be done with a very limited number of data and in an online manner. This research lies at the intersection of various fields: reinforcement learning, probabilistic machine learning, human-AI interaction, multiagent systems, cognitive modelling etc.

Keywords

Human-AI interaction, Multiagent models, Reinforcement learning

Contact Person

Prof. Dr. Pierre-Alexandre Murena
Email: pierre-alexandre.murena@tuhh.de

Website

Website: https://www.tuhh.de/human-ai/homepage

About the Insitute

The Institute for Ethics in Technology is committed to pioneering research and education at the intersection of ethics, analytic philosophy, and technological innovation. Our ambition is to integrate the rigour and insights from philosophical ethics and humanistic inquiry into all phases of technological development, implementation, and use, especially those connected to artificial intelligence. The three core pillars of our work are research, teaching, and knowledge exchange.

Research: We are committed to advancing cutting-edge research that pushes the boundaries of ethical understanding in technology, fostering a landscape where innovation and ethics can walk hand in hand.

Teaching: Our teaching programs and educational activities help prepare the next generation of engineers, decision-makers, and technology leaders for the ethically complex environments they will face.

Knowledge exchange: We facilitate dialogues and partnerships across various sectors including society, politics, policy, and industry. Our engagement initiatives serve as a platform for exchanging knowledge, fostering collaboration, and ensuring that ethical considerations can be more easily integrated into real-world applications.

Contact Person

Prof. Maximilian Kiener
maximilian.kiener@tuhh.de 
Phone: - 3149

Website

 https://www.tuhh.de/ethics/willkommen