0701 Research Seminar in Semantic Artificial Intelligence
Dr. Fajar Juang Ekaputra
Contact details
Weekly hours
Language of instruction
09/07/23 to 09/27/23
Registration via LPIS
Notes to the course
Day Date Time Room
Friday 10/13/23 09:00 AM - 01:00 PM D2.0.030
Thursday 11/23/23 09:00 AM - 05:00 PM D2.0.330
Tuesday 01/16/24 09:00 AM - 05:00 PM TC.3.11

The content of this course revolves around conducting a first scientific work and the preparation of a scientific paper about this work (in English).

The students will receive concrete tasks as part of an ongoing research project involving data collection (individual), data synchronisation(in groups) and data analysis (individual). Based on the results of these tasks, to students will write up a scientific paper.

 For mutual feedback, a scientific peer review system will be adopted. Students will be assigned 2 papers of their colleagues and write a review for each of those, in which they give an expert opinion on the manuscript. The final report, also integrating the revisions to address the reviews’ remarks, has to be submitted before the end of the semester.

Learning outcomes

  • Time management and presentation techniques
  • Understanding of scientific work and literature search
  • Presentation of research topics
  • Preparation of scientific papers
Attendance requirements

The in-class (offline) attendance is compulsory the whole first and last lecture.

During the second class, in-class (offline) individual and group appointments are established that must not be missed. 

Teaching/learning method(s)

Conducting research tasks such as data collection and analysis. Preparation of a seminar paper, presentation, discussion, assessment.


Data collection and consolidation: 25%

First version of the seminar paper and presentation of the research results: 30%

Peer-review: 15%

Final seminar paper: 30%

Prerequisites for participation and waiting lists

Positive completion of course 1 of the “Knowledge Management” SBWL. The presence in the first unit of the course is a compulsory prerequisite.


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Recommended previous knowledge and skills


Availability of lecturer(s)

via Email

Last edited: 2023-10-09