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Student Projects: Theses, Studienarbeiten and Project Groups
To handle the large number of requests for student projects, future Bachelor and Master Theses as well as Studienarbeiten will be supervised by PhD students with feedback to Prof. Möller in larger time periods. The table below shows our current group members, their availability to supervise theses, and the topics/areas they offer theses in. In case you are interested, please contact us via the E-Mail-address cv_student_projects (at) eti.uni-siegen.de and answer all questions below. We will then assign you to a supervisor. Note that prior knowledge in our fields of research (e.g. gained by attending the chair's lectures) is a requirement to be able to write a final thesis with us (in particular a completed course in Machine Learning or Deep Learning is a requirement)! We do not offer internships.
|
PhD |
Available Slots |
Topic / Area |
|
Vaishnavi Gandikota |
Fully occupied |
Generative models and deep learning applications in image reconstruction |
|
Marcel Seelbach |
Fully occupied |
Optimization methods using quantum computing |
|
Marius Bock |
Fully occupied |
Wearable & Video Human Activity Recognition |
|
Alexander Auras |
Fully occupied |
Inverse problems and regularization methods |
|
Jan Philipp Schneider |
Fully occupied |
Joint optimization methods for (physical) system and network parameters; Incorperating physical knowledge within deep learning models |
|
Michael Schopf-Küster |
Fully occupied |
i) 3D shape completion; |
|
Dr. Jovita Lukasik |
2 slots free |
Neural Architecture Search and Robustness |
| Dr. Natacha Kuete Meli | 2 slots free | Quantum Computing for Computer Vision |
Questions
1. Which study program are you enrolled in? Do you want to write a Studienarbeit, Project group, Bachelor or Master thesis?
2. Which open topics (see table) are you interested in?
3. Which ML-related courses have you taken?
4. Can you please attach your transcript of records (this is the list of your courses and grades you can get from Unisono)? You can also attach your CV (this is appreciated, but not required).
5. Which courses are you taking which are not yet in the transcript of records?
6. Which ML-related projects have you done so far (in Siegen or elsewhere)?
7. If you have worked with our/ another group during a project/ Hiwi Job, you can leave a reference.
For questions 8-11, please grade your abilities (0: never heard of, 10: expert) for the following areas. Particularly for demonstrating your coding experience, you can share with us e.g your Github account:
8. Coding skills:
i) Python,
ii) Deep learning frameworks (like Pytorch, Tensorflow,...),
iii) C/C++,
iv) Matlab.
9. Ability to read and understand a scientific/ Deep learning paper.
10. Ability to get another's code (e.g. from a GitHub repository) running.
11. Formal background, linear algebra/optimization/ general math topics.
Industry theses
Industrial theses are a special case and not frequently offered by our group. One reason is that the objectives of industry theses often do not directly align with our research. In particular, our interest lies in publishing papers and/or defining projects well suited for PhD thesis (with third-party funding). Thus, we decide about industry theses on a case-by-case basis with the following aspects being crucial:
1. Our group will not supervise theses under a non-disclosure agreement (NDA), except for exceptional cases of long-term collaborations with clear and realistic (short-to-medium-term) perspectives on how the group benefits from the thesis, e.g. in form of funding/joint third-party-funding applications.
2. Speak with us about the topic and the time schedule as early as possible! The topic will be assigned by the university, not the company!
3. The goal of the master thesis is to demonstrate the ability to conduct research, i.e., create previously unknown insights and/or new approaches to certain problems. Naturally, an industry thesis has to fulfill these scientific requirements in the same way as a thesis written at the University.