Novel and non-mainstream advances in Data Science
- Typ: Seminar (S)
- Lehrstuhl: KIT-Fakultät für Informatik - Institut für Programmstrukturen und Datenorganisation - IPD Böhm
- Semester: SS 2023
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Ort:
Raum 348 (3. Stock)
50.34 INFORMATIK, Kollegiengebäude am Fasanengarten -
Zeit:
Kick Off Meeting: 21.04.2023 from 10:00 - 12:00
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Dozent:
Prof. Dr.-Ing. Klemens Böhm
Pawel Bielski - LVNr.: 2400110
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Hinweis:
Please register at sekretariat.boehm@ipd.kit.edu
The dates during the semester are arranged individually and flexibly with the supervisors. As a rule, these are 2-3 dates plus the final event.
Content:
This seminar aims to teach the students about the principles of research work. It includes finding and organizing scientific knowledge, creating powerful presentations, and writing scientific reports. The students will work under the guidance of the Ph.D. students on state-of-the-art research topics from the area of Data Science, such as:
- combining domain knowledge with machine learning
- kernel-based machine learning
- data encoders
- active learning
- surrogate machine learning
- finite element analysis with machine learning
At the end of the semester, the students will present all the topics to the whole seminar group. As a result, every student will additionally get insights into various topics that will widen their horizons and make them more aware of the state-of-the-art advances in Data Science.