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Emerging Topics in Machine Learning and AI

Hauptseminar für Master-Studiengänge
im Wintersemester 2022 (LMU, TUM IN0014, IN4422)

Prof. Dr. D. Kranzlmüller
Dr. Andre Luckow
Dr. Karl Fuerlinger

Welcome to the Master's Seminar on "Emerging Topics in Machine Learning and AI" in the winter term 2022/23. Here you will be able to find all the details concerning the seminar.


  • 03.02.2023: The seminar presentations are available in the download section.
  • 01.02.2023: Agenda for Seminar
  • 01.02.2023: The block seminar will take place on Saturday, Feb 4, 2023, in room 161, from 09:00 c.t. to approx. 14:00 Uhr
  • 27.01.2023: Paper collection available online.
  • 25.01.2023: The slides for the presentation lecture are available.
  • 21.01.2023: The presentation lecture will take place on Wednesday, 25.01., 4pm c.t., in Room 161.
  • 10.12.2022: Review Assignments and Papers online
  • 22.10.2022: The scientific work lecture will take place on Oct. 26, 2022, 4pm c.t. Zoom Link (Meeting ID: 924 3931 3159, Passcode: 250369)
  • 22.10.2022: Topic Assignment has been published. Please email us in case of questions. Open topics that could be swapped: 5, 11, 12.
  • 15.10.2022: Please ensure that you attend the introduction class on Oct. 19. We will assign all seminar slots in this class.
  • 27.07.2022: The introduction lecture is scheduled to take place on October 19th, 4pm CET c.t. at Oettingenstr. 67, Room 161.
  • 27.07.2022: Welcome to the website of the seminar "Emerging Topics in Machine Learning and AI" in the winter term 2022/23!

Inhalt des Seminars


Machine Learning (ML) and Artificial Intelligence (AI) are transformational technologies that will have a significant impact on science and business. The aim of this seminar is to give the student an overview of the topics of data & compute infrastructures, machine learning and AI. The aim is to develop a technical understanding of large-scale systems and infrastructures for data infrastructures and advanced analytics. The students deepen their computer science knowledge in a practice-oriented way and with methods, techniques, procedures, tools and infrastructures for the processing and analysis of large data:

  • Machine Learning (Methods & Tools: Tensorflow and Pytorch)
  • Deep Learning: Convolutional Neural Networks (ResNet, Yolo, SSD)
  • Natural Language Processing: Word Embeddings, Language Models (RNNs, LSTMs, Transformers), Knowledge Graphs
  • Scalable Machine Learning: Distributed Training, AI Hardware
  • Quantum Machine Learning: Variational Algorithms, Optimization
  • Emerging Machine Learning Applications in Computer Systems, Cybersecurity and Fault Tolerance
  • Responsible AI: AI Ethics, Robust AI



The seminar will be based on the metaphor of a conference. Students will prepare a conference paper (technical report) on a chosen topic and will submit it to the seminar organizer (the fictitious program committee), receive an assessment of their submission from a supervisor and present (possibly corrected) paper at the fictitious conference at the end of the semester. After the first version of the paper has been submitted, each participant will be assigned two papers to review (according to a review given template, so that each paper will receive two reviews. This should increase the quality of the elaborations and familiarize the participants with the process of a scientific publication process. After the review, the authors have another 2 weeks to address the obtained comments/suggestions. Both the quality of the reviews and the implementation of the comments will be considered in the grading process.

The conference itself, in which all presentations are held, is designed as 1 to 2 day event at the end of the term. The exact date and the agenda will be announced on this website.

The introduction event for all seminar participants will take place in the first or second lecture week. Only in this event the topics are assigned. Participation in the introduction event is obligatory for all participants.

Important: Everyone who does not participate in the introduction event will lose his seminar seat due to the great demand!

The seminar will be held in English.

In the course of the semester, mandatory lectures on scientific work, presentation techniques are scheduled. The Latex lecture is voluntary.

Please review the guidelines for the creation of scientific papers: Guidelines for seminar and scientific papers.

Please use the provided Latex and presentation templates (Powerpoint, Latex).

Formal Criteria

The final grade of the seminar is determined by the quality of the scientific paper, presentation, the contributed reviews, and participation in the seminars.


The paper must meet the following criteria:

  • Use of the Latex Template IEEE(see Downloads)
  • Scope: minimum 6 to 8 pages
Non-conformance to one of the criteria will negatively impact the final grade!

Peer Review:

Participation in the review process is obligatory for the successful completion of the seminar! The quality of the review will be considered in the final grade.

Participation in the review process is obligatory for the successful existence of the seminar! Failure to submit a review will negatively impact the final grade


The final presentation during the block seminar should not be longer than 12 minutes. It is planned to have a 5-8 minute Q&A session after each talk. Please use one of the suggested templates when prepairing your slide decks.

Participation in the complete block event is obligatory for all participants of the seminar!
The use of the wrong template will negatively impact the final grade.

NOTE: Once participation has been confirmed (i.e., a topic has been chosen and agreed to be presented with the supervisor) there will be no possibility to leave the event without the corresponding participation being considered as unsuccessful (i.e. student gets 5.0). No-show for the final presentation will also be considered as an unsuccessful participation.


You will find all availabe topics here: Seminar Topics


Event Dates:

  • 19.10.2022, 4pm c.t.:Introduction and Topic Assignment (in-person, room 161)
  • 26.10.2022, 4pm c.t.:Scientific Work und LaTeX Tutorial (online)
  • 25.01.2023, 4pm c.t.:Presentation Lecture (in-person, room 161)
  • 04.02.2023, 9am - 6pm c.t.: Block Seminar (Saturday, in-person, room 161)

Important Dates:

  • 21.10.2022, 11:59pm s.t.: Submission of the Topic Preferences
  • 23.10.2022, 11:59pm s.t.: Topic Assignments
  • 04.11.2022, 11:59pm s.t.: Submission of the Outline
  • 09.12.2022, 11:59pm s.t.: Submission of Paper
  • 10.12.2022, 11:59pm s.t.: Peer Review Assignements
  • 23.12.2022, 11:59pm s.t.: Submission of Reviews
  • 25.01.2023, 11:59pm s.t.: Submission of final paper
  • 01.02.2023, 11:59pm s.t.: Submission of final presentation
All artifacts must be submitted to Uni2Work. In the case of a system error, please send your documents via e-mail to your supervisor and to the organizing team of the seminar:


Questions, criticism and suggestions are always welcome. Please use the seminar-specific e-mail address

Tipps zur Bearbeitung


  1. LaTeX-Vorlage IEEEtran
  2. Notes on Paper Writing
  3. Review-Vorlage
  4. Peer Review Guidelines
  5. Grading Criteria
  6. Slides Introduction
  7. Topic Assigments
  8. Slides Scientific Work
  9. Submissions
  10. Peer Review Assignments
  11. Presentation Lecture
  12. Seminar Paper Collection
  13. Agenda for Seminar
  14. Presentations