The chair of artificial intelligence deals with the wide field of machine learning. In particular the chair concentrates on the development and implementation of learning algorithms that solve challenging problems.
The chair Computer Science VIII Artificial Intelligence has new web pages:
The LS8 secretariat will not be staffed from 24.12.2022 to 08.01.2023 inclusive. During this time, the TU Dortmund University will be completely closed.
With good wishes for a peaceful Christmas season and a confident, healthy start into the year 2023! LS8 team
The Stanford statistician John Ioannidis publishes a list of the 100,000 most influential scientists (science-wide).
In the single-year ranking of the current version (based on the data for the year 2021, published November 2022), Prof. Schubert ranks 92735.
TU Dortmund has 17 members in the top 100,000, led by Erman Tekkaya (mechanical engineering, #25235) and Oliver Kayser (biochemistry, #38430). Our rector Manfred Bayer (physics, #87172) is included as well as Boris Otto (industrial information management, #78427), another professor co-opted in Computer Science. Almost in the top 100.000 is Günter Rudolph (#105622).
The ranking is based on Elsevier's Scopus data and the composite citation index (c-score) developed by the Stanford statistician John Ioannidis. The index combines scaled citation numbers (without self-citations), h-index and hm-index, but also uses the author order. Nevertheless, any such ranking is based on design choices and data that may be biased, e.g., the Elsevier Scopus data use to be journal-oriented and not value compute science conferences as much.
The similar "career-long" ranking contains 19 members of the TU Dortmund, including the three computer scientists Günter Rudolph (#43603), Ingo Wegener (#67497) and Bernhard Steffen (#75346).
Amal Saadallah has defended her dissertation Explainable Adaptation of Time Series Forecasting with great praise (magna cum laude). In her work, she focuses on the online management of many models for time series forecasting, the combination of Machine Learning methods and process simulation systems, and explainable model-based quality prediction in Industry 4.0.
The members of the Ph.D. committee were Prof. Dr. Katharina Morik (supervisor and first reviewer), Prof. Dr. Barbara Hammer (second reviewer, Bielefeld University), Prof. Dr. Petra Wiederkehr (chair) and Jun.-Prof. Dr. Thomas Liebig (faculty representative). Amal Saadallah is a research associate at the LS8 and member of the Collaborative Research Center 876 (project B3).
Lukas Pfahler has defended his dissertation Some Representation Learning Tasks and the Inspection of Their Models with distinction (summa cum laude). In his work, he focuses on representation learning with unsupervised methods. For instance, he has investigated the use of embedding learning with graph convolutional neural networks for the search and retrieval of related mathematical expressions. Furthermore, he has worked on novel methods for model inspection to increase trust in decisions.
The members of the PhD committee were Prof. Dr. Katharina Morik (supervisor and first reviewer), Prof. Dr. Andreas Hotho (second reviewer, University of Würzburg), Prof. Dr. Jakob Rehof (chair) and Priv.-Doz. Dr. habil Frank Weichert (faculty representative). Lukas Pfahler is a research associate at LS8 and member of the Collaborative Research Center 876 (project A1).
Mirko Bunse has defended his dissertation Machine Learning for Acquiring Knowledge in Astro-Particle Physics with great praise (magna cum laude). In his work, he studied the manifold applications of Machine Learning algorithms in Astroparticle Physics. In particular, he focuses on the smart and resource-aware control of simulations through active class selection and the domain-specific aggregation of predictions in terms of quantification and unfolding.
The members of the PhD committee were Prof. Dr. Katharina Morik (supervisor and first reviewer), Dr. Fabrizio Sebastiani (second reviewer, Consiglio Nazionale delle Ricerche, Pisa), Prof. Dr. Johannes Fischer (chair) and Jun.-Prof. Dr. Thomas Liebig (faculty representative). Mirko Bunse is a research associate at LS8, member of the Collaborative Research Center 876 (project C3) and Coordinator of the application field astroparticle physics at the Lamarr Institute for Machine Learning and Artificial Intelligence (former Competence Center ML2R).
The 3rd trilateral AI symposium of Japan, Germany and France took place the 27th of October 2022 in Tokyo. Katharina Morik organized the session “Smart Cities” in which 2 speakers of each country presented their work. She presented the EU projects INSIGHT and VAVEL (coordinator. Dimitrios Gunopoulos), in which she participated together with Thomas Liebig. The concluding discussion stressed as most important the acquisition of mobility data and the interaction of all the stakeholders. How should mobility companies, governmental institutions, IT companies and the users cooperate?
At the SISAP 2022 conference at the University of Bologna, Lars Lenssen won the "best student paper" award for the contribution "Lars Lenssen, Erich Schubert. Clustering by Direct Optimization of the Medoid Silhouette. In: Similarity Search and Applications. SISAP 2022. https://doi.org/10.1007/978-3-031-17849-8_15".
The publisher Springer donates a monetary prize for the awards, and the best contributions are invited to submit an extended version to a special issue of the A* journal "Information Systems".
In this paper, we introduce a new clustering method that directly optimizes the Medoid Silhouette, a variant of the popular Silhouette measure of clustering quality. As the new variant is O(k²) times faster than previous approaches, we can cluster data sets larger by orders of magnitude, where large values of k are desirable. The implementation is available in the Rust "kmedoids" crate and the Python module "kmedoids", the code is open source on Github.
The group is successful for the second time: In 2020, Erik Thordsen won the award with the contribution "Erik Thordsen, Erich Schubert. ABID: Angle Based Intrinsic Dimensionality. In: Similarity Search and Applications. SISAP 2020. https://doi.org/10.1007/978-3-030-60936-8_17".
This paper introduced a new angle-based estimator of the intrinsic dimensionality – a measure of local data complexity – traditionally estimated solely from distances.
Sebastian Buschjäger has defended his dissertation Ensemble Learning with Discrete Classifiers on Small Devices at the Chair of Artificial Intelligence with distinction (summa cum laude). He conducted research on the topic of resource-aware machine learning in the context of the Collaborative Research Center 876, Project A1. He researched ensemble methods in the context of embedded systems. This included training as well as deploying decision forests on small devices.
The members of the PhD committee were Prof. Dr. Katharina Morik (supervisor and first reviewer), Prof. Johannes Fürnkranz (second reviewer, University of Linz), Prof. Dr. Jian-Jia Chen (chair) and Prof. Dr. Jens Teubner (faculty representative). Sebastian Buschjäger is a research associate at LS8 and a member of the Collaborative Research Center 876 (Project A1).
The technology pioneer for autonomous driving, Prof. Sebastian Thrun, was honored as "Vordenker 2022" at Goethe University Frankfurt on September 15. The former Google vice-director and Stanford professor founded the online learning platform Udacity and is now dedicated to autonomous flying. In his speech, he recognized Katharina Morik as a leading pioneer in the field of artificial learning. Prof. Thrun said she "was already the goddess of artificial learning back then. The very first one who did it in Germany and is still quite a leader today." In the panel, Prof. Morik explained how artificial intelligence can help make work more productive, safe and environmentally friendly, creating capacity for social good. The director of the Lamarr Institute for Machine Learning and Artificial Intelligence also presented Lamarr's research on intelligible communication of artificial intelligence in the form of so-called care labels.
A recording of the event is available online:
(more information )
As of July 1, 2022, the Competence Center ML2R, which is constituted by the Chair for Artificial Intelligence at TU Dortmund University, the Fraunhofer Institutes IAIS and IML as well as the University of Bonn, enters into long-term institutional funding by the German federal government and the state of North Rhine-Westphalia. The Lamarr Institute for Machine Learning and Artificial Intelligence builds on the successes of ML2R and is dedicated to the value-based research and development of high-performance, trustworthy as well as resource-efficient Artificial Intelligence.
TU Professor Katharina Morik will again serve as co-director of the new international AI Center of Excellence. The Lamarr Institute is one of five German AI competence centers that were previously funded as projects and will now receive permanent, institutional funding. Together with the DFKI, they form the nucleus of German AI research.
Get first insights into the Lamarr Institute: https://lamarr-institute.org/
(more information )We've all heard it before: AI is taking away our jobs! - But is that true? On 07.04.2022 4 experts, moderated by Katja Scherer, met to discuss the topic and to show possibilities how we as a society can deal with the technological innovation.
The Chair VIII of the Faculty of Computer Science has an immediate vacancy for a student assistant (SHK / WHF) in the field of Federated Learning. The number of hours can be discussed individually. The offer is aimed at students of computer science who have completed their studies with very good results.
You can find more information about the positions and your application here
The Chair VIII of the Faculty of Computer Science has immediate vacancies for student assistants (SHK / WHF). The number of hours can be discussed individually. The offer is aimed at students of computer science who have completed their studies with very good results.
You can find more information about the positions and your application here
