We are happy to announce the dataninja.nrw inauguration event that takes place virtually on Monday, May, 3rd, 16-18.

Our research group at TH Köln is part of the AI graduate college dataninja.nrw with a PhD tandem together with Ruhr University Bochum.

Please see the attached PDF dataninja_inauguration_05_03 for all the details and the programme of the inauguration event and how to register.

All interested people are free to join this event!

We are happy to announce that Samineh Bagheri won the Dissertation Price 2020 of TH Köln for her PhD thesis. Her thesis “Self-Adjusting Surrogate-Assisted Optimization Techniques for Expensive Constrained Black Box Problems” deals with state-of-the art optimization algorithms supported by RBF surrogate models.

The award ceremony took place online - as usual in these times - on Monday, Feb, 22nd, 2021, and was conducted by vice president Prof. Klaus Becker (upper row, right), attended by all other members of the presidential committee, including president Prof. Stefan Herzig (upper row, left) and of course the laureate Dr. Samineh Bagheri (lower row, left) and her supervisor Prof. Wolfgang Konen (lower row, right).

Read more about the dissertation price and Samineh Bagheri in this THK-News (sorry, in German only!)

Read more about Samineh's PhD-colloquium (the first fully-online colloq at Leiden University) in this CIOP blog post.

We are happy to announce that the CIOP group of TH Köln participated with two papers and two talks at the 9th International Conference BIOMA'2020 (Bioinspired Optimization Methods and Applications), which took place November 2020, 19th-20th, and was this year a completely online event:

  1. "Reinforcement Learning for N-Player Games: The Importance of Final Adaptation" by Wolfgang Konen and Samineh Bagheri. The talk presented a new approach for game learning and game playing on a variety of games with 1, 2 and 3 players.
  2. "Time Series Encodings with Temporal Convolutional Networks" by Markus Thill, Wolfgang Konen and Thomas Bäck. The talk presented a deep learning approach for anomaly detection of otherwise hard-to-find temporal anomalies in time series.

Although a fully-online event, the single-track conference took place in a nice atmosphere, with many discussions and informal chats. A side effect of the online format was that each speaker was asked to record a backup video, which could be played in case of technical problems. Thus, if you missed the conference, you can nevertheless take a look at the paper, the slides and the video, if you like:

  1. "Reinforcement Learning for N-Player Games: The Importance of Final Adaptation": paper, slides, video (15 min)
  2. "Time Series Encodings with Temporal Convolutional Networks": paper, slides, video (15 min)


The State of North Rhine-Westphalia provides a grant for the AI Graduate College Data-NInJA („Trustworthy AI for Seamless Problem Solving: Next Generation Intelligence Joins Robust Data Analysis“), coordinated by Prof. Barbara Hammer, University Bielefeld. The grant consists of seven PhD tandems, which were selected out of 37 applications for this grant by an expert jury.

TH Köln takes part in this Graduate College with a PhD tandem together with Ruhr-University Bochum (RUB). Under the title „(RL)³: Representation, Reinforcement und Rule Learning“ the research is conducted by Prof. Laurenz Wiskott from the Neuroinformatics Institute, RUB, and Prof. Wolfgang Konen from the Cologne Institute of Computer Science, TH Köln, together with two PhD students at each institution. The reseach aims at explainable and interpretable AI models, where methods from (deep) reinforcement learning and representation learning will play an important role. The new element of this research project is that both PhD students, one at RUB and one at TH Köln, will work closely together in the PhD tandem, together with their supervisors.

First Place in Opitz Reward 2020 for Jordan Scholzen (Source: Jordan Scholzen / TH Köln)

Jordan Scholzen got with his Bachelor's thesis "Künstliche Intelligenz in der Kompositionslehre - Eine Untersuchung von Long-Short-Term-Memory-Netzen zur Analyse von Kontrapunkten nach Fux" the first place in the Opitz-Innovation Reward 2020. The thesis, supervised by Prof. Dr. Wolfgang Konen, investigates how a supportive AI for music scholars studying composition can look like. Scholzen showed that neural networks of LSTM type allow to learn whether a certain musical line in a counterpoint violates or adheres to the rules once formulated by famous baroque music instructor Johann Joseph Fux.

It is characteristical and shows the importance of the area AI that all 3 Opitz rewards in 2020 covered themes connected with AI. More about Opitz-Innovationspreis 2020 (sorry, in German only) can be found here. The full Bachelor's thesis (again sorry: only German) can be found