Research Projects and Practicals Machine Learning
Research projects and practicals in machine learning are intended to give students an opportunity to get engaged in research conducted in one of the groups and labs participating in the ML Master study program, for the duration of one semester. Students will gain practical experience in designing and programming methods / software / tools for ML. They will be able to use libraries and frameworks, and will acquire knowledge or extend their knowledge of various programming languages. Students obtain teamwork and collaboration skills, and they will learn about project organization and presentation techniques. Students will know about the strengths and weaknesses and about the limitations of various methods for evaluating complex and high-dimensional data, and will be able to describe and evaluate these methods. Performance is evaluated based on active participation, a presentation of results and in written reports. Students are closely supervised by an AVG team member and present their progress in monthly student spotlights to the entire group.
Research Projects Machine Learning:
- 9 ECTS, 270 h
- Conducted individually
Practicals Machine Learning:
- 6 ECTS, 180 h
- Conducted in a small team of 2-5 students
If you are interested in doing a research project or practical with us, please follow these steps:
- You must be in the second semester or higher of the ML master program, with very good grades.
- You need to have a solid math (analysis, algebra, statistics) and programming (python, PyTorch) background and prior experience in machine learning or computer vision. If you don't, please take the relevant courses before approaching us.
- Familiarize yourself with our latest research (last 2 years). You find all abstracts of our recent publications on this page. Read the papers that you find most interesting and think about potential extensions.
- Send an email to Prof. Andreas Geiger that describes your programming experience, your research interests and your project ideas, if you have any. Mention the papers from us that you find most interesting and send us your comments/ideas. Please also attach your CV and transcripts.
Based on this information, we will match you to one of our research projects.