Seminar/Proseminar: Machine Learning for Process Control

Numerous real-world processes need to be kept under control in order to ensure safety or efficiency. Machine learning models are good candidates for this. They can for example detect shifts/anomalies/decalibrations/instabilities/etc. and possibly also predict which action needs to be taken on the process. The real-time nature of such tasks brings unique challenges from a ML perspective compared to classical application of ML. This seminar will explore relevant ML methods such as online/reinforcement learning and real-time data analysis. Use cases in manufacturing and intensive care will be covered.

Students will select a few papers from a pool of thematically relevant research papers, which they will read and present over the course of the semester.

Kick-off meeting: Friday 27 October 2023 at 16:15 in room T9/049 Seminarraum (Takustr. 9)

Information about the course: here

Presenter-Paper matching:

Siyu Deng:
 - Yoon et al. AI in critical care medicine, 2022

 Se Yeon Kim:
 - Li et al. Towards intelligent monitoring system in WAAM, 2022

Nathan Ritter:
 - Yoon et al. AI in critical care medicine, 2022

Jakob Isai Knitter:
 - Au-Yeung et al. Real-time ML-based ICU alarm classification [...], 2021

Julian Hesse:
 - Wang et al. Active disturbance rejection control of layer width in WAAM based on DL, 2021