Interdisciplinary Project in Data Science

Project addressing a domain-specific challenge

Steps for the Interdisciplinary Project in Data Science

1. Select a main supervisor for the project

• Usually not from the Faculty of Informatics (or Mathematics)
• Not necessarily from the TU Wien
• A list of possible names is below, but you are not restricted to this list

2. Discuss the project with the selected supervisor and agree on a 1-page outline

3. Select a co-supervisor for the project

• Usually from the Faculty of Informatics (or Mathematics)
• Must be from the TU Wien
• E.g., anybody that has lectured any of the Data Science courses

4. Discuss the 1-page outline with the co-supervisor

5. Refine the outline until both supervisors agree

6. Do the project

7. Discuss regularly with the supervisors

8. Write the report    

Potential Main Supervisors

If no topic is given in the list below, see the Interdisciplinary Lecture Series talk for details on the topic:

• Dominik Eder (dominik.eder@tuwien.ac.at)
• David Garcia (garcia@csh.ac.at) - Computational Social Science
• Andreas Grüneis (andreas.grueneis@tuwien.ac.at)
• Peter Klimek (peter.klimek@meduniwien.ac.at)
• Georg Madsen (georg.madsen@tuwien.ac.at)
• Günther Tschabuschnig (Guenther.Tschabuschnig@zamg.ac.at)
• Markus Valtiner (Markus Valtiner@tuwien.ac.at)
• Tina Wakolbinger (Tina.Wakolbinger@wu.ac.at)

Steps in the Module “DSA – Domain-Specific Aspects of Data Science”

1. Attend the Interdisciplinary Lecture Series on Data Science (194.046)
2. Choose an area
3. Get theoretical knowledge through attending a lecture in this area (3,0/2,0 VO/VU/SE Fachspezifische Lehrveranstaltungen)
4. Solve a practical problem in inter-disciplinary project work – Interdisciplinary Project in Data Science (194.060/194.047)