Advanced Seminar (EI7742)

  • Master EI
  • 5 ECTS
  • English
  • winter and summer term
  • max. 6 participants
  • one-on-one supervision
  • includes tutorials on literature research, scientific writing and giving effective talks


The goal of the advanced seminar is to develop basic skills in literature research, scientific writing, and giving scientific talks, next to understanding the process of scientific publishing. During this module, your task is to write an academic paper on a topic of your interest, under the supervision and coaching that we offer. At the end of the module, all papers will be presented and discussed in a conference-like get-together.

The topic of this seminar changes every semester according to recent technical trends, but it is always in the broad area of embedded and/or real-time systems. The seminar gives you the opportunity to practice working in a scientific manner, to get individual feedback, and to improve skills that are beneficial for your Master's Thesis or an academic carreer.

Topics in Summer Term 2020

The main topic of this semester's seminar will be "Deep Learning in Embedded Systems". The topics offered are:

  1. Computational requirements/characteristics of deep/machine learning (assigned)
  2. Hardware design/architecture for deep learning (assigned)
  3. Applications of deep learning
  4. Deep learning on resource-constrained systems
  5. Deep learning algorithms (assigned)
  6. Criticism/alternatives to deep learning
  7. Security in deep learning-based systems (assigned)

Important Dates

The mandatory kick-off meeting will take place April 24th (Friday) at 13.15 in our advanced seminar chat room or via video conference tool, as meeting in person will not be possible until then. I will let you know how the exact procedure in time.

If there are any other changes due to the corona virus spread, we will inform you as soon as possible. Please excuse any inconvenieces that might occur due to the current situation, this is a challenge for everyone!


The registration happens via email and personal discussion, not via TUMonline (first come, first serve). If you are interested in one of the topics, please contact:

Nadja Heitmann