Research Seminar on Artificial Intelligence (RSAI)

  Logo AI-Center and IoP

The AI expert group from the Cluster of Excellence “Internet of Production” (IoP) and the AI Center are launching a biweekly research seminar. This series of events provides a space for Ph.D. researchers and postdocs to present their AI-related research to the IoP and AI community of RWTH.


Mailing List

E-mail with subject "subscribe" to



+49 241 80 92062



The seminar has the objective of increasing the understanding of the AI research conducted within the IoP cluster in particular and at RWTH in general. Through this understanding, we want to allow participants to form an idea of the current challenges that have to be tackled as well as the state-of-the-art techniques in this field. By connecting researchers who work on AI methods with those who work on possible applications, the research efforts at RWTH can be bundled and strengthened.

Starting on the 29th of June, the AI seminar will be a roughly biweekly event, which takes place on Tuesdays at 4 pm. Each event consists of a 30-minute presentation regarding a research topic followed by a discussion of roughly 15 minutes. The presentations will have a strong focus on AI methods such as machine learning, symbolic AI, or process mining. All events already scheduled will be announced on this website.

The seminar is jointly hosted by the RWTH Cluster of Excellence “Internet of Production” (IoP) and the RWTH AI Center. The events are organized by the AI expert group of the IoP, which is led by the Knowledge-Based Systems Group (KBSG, Prof. Lakemeyer) and the Institute for Data Science in Mechanical Engineering (DSME, Prof. Trimpe). To stay up to date with information regarding the AI seminar, you can subscribe to its mailing list by sending an e-mail with the subject "subscribe" to



The seminar is mainly focused on scientists associated with the IoP and the AI Center, who present their research in the talks. Researchers from other areas who would like to present at the seminar are encouraged to contact us. The audience consists mainly of researchers, master students and professors from RWTH and other affiliated research facilities (e.g., FZ Jülich). In some cases, it might be possible for externals to attend a particular event. If you are interested, please get in touch with the organizers!

Date Speaker (Institute) Topic
2021 All speakers of 2021 Research Seminar on AI 2021
30.11.2021 Muzaffer Ay, M.Sc. (Institute of Automatic Control)

Potentials and Challenges of Data-based Approaches in and around Model-predictive Quality Control

14.12.2021 Mahsa Pourbafrani, M.Sc. (Chair of Process and Data Science) Explainable AI in practice: Remaining Time Prediction for Processes with Inter-Case Dynamics
22.02.2022 Jan Tönshoff, M.Sc. (Chair for Logic and Theory of Discrete Systems) Graph Learning with 1D Convolutions on Random Walks
08.03.2022 Giacamo Borghi, M.Sc. (Energy Entropy and Dissipative Dynamics)

Kinetic Theory for Metaheuristic Optimization Algorithms

22.03.2022 Denny Thaler, M.Sc. (Institute für General Mechanics) Training Data Selection for Machine Learning-Enhanced Monte Carlo Simulations in Structural Dynamics
19.04.2022 Dr. Youness Boutaib (Chair for Mathematics of Information Processing) Path Classification by Stochastic Linear Recurrent Neural Networks

Josina Schulte, M.Sc. (Chair of Experimental Physics III A)

Inference of Cosmic-Ray Source Properties by Conditional Invertible Neural Networks

Paul Zheng, M.Sc. (ISEK)

Federated Learning in Heterogeneous Networks with Unreliable Communication
14.06.2022 Florian Frantzen, M.Sc. (Computational Network Science) Outlier Detection for Trajectories via Flow-embeddings
28.06.2022 Oliver Rippel, M.Sc. (Institute of Imaging and Computer Vision) Deep Anomaly Detection for Automated Visual Inspection
12.07.2022 Martin Unterberg (Chair of Manufacturing Technology) Unsupervised Tool Condition Monitoring in Fine Blanking
August Summer Break
06.09.2022 Paul Buske, M.Sc. (Chair for Technology of Optical Systems) Advanced Beam Shaping for Laser Materials Processing Based on Diffractive Neural Networks
20.09.2022 Florian Brillowski, M.Sc. (Institut für Textiltechnik)

When Algorithms Learn Like Humans - Can Curricula for Machine Learning Help to Tackle Data Scarcity?


Mona Buisson-Fenet, M.Sc. (Institute for Data Science in Mechanical Engineering)

Recognition Models to Learn Dynamics from Partial Observations with Neural ODEs