If you are interested in writing a BSc / BEng / MSc thesis in our group, please review the following information:

1. You should have attended relevant courses in the field of machine learning (e.g., 02451, 02452, 02460, 02456, 02477), and also have a good background in mathematics (calculus/statistics/linear algebra).

2. I focus on the following research topics. Please check if any of these resonate with your interests.

3. Please send an email with the following information:
- Transcript of records and current study status.
- Relevant courses / projects / experience in machine learning.
- Timeline (start and duration) and number of ECTS.
- Which topic are you considering.

Ideally, you should work on one of the suggested topics, and we will discuss particular ideas when we meet. If you have another idea, you should provide a short description, describing the problem, related literature, your planned approach / method, access to relevant data, etc. This process (usually) takes a couple of weeks, so please be proactive.

Suggested topics:

* Deep learning theory. One of the most interesting challenges is understanding why deep learning models generalize so well on unseen data.

* Optimization techniques. The properties of optimization algorithms influence the behavior of modern machine learning models.

* Generative models. Learning the geometry of the manifold that approximates the data enhances representation learning and statistical modeling.

We run a reading group focused on recent papers and foundational topics in machine learning.

We meet weekly to present and discuss papers, share ongoing work, and exchange ideas in an informal setting. Students who are curious about the field are very welcome to join, even if only to listen.

If you would like to join, please send me an email with your CV and transcripts.