The inIT and the Promotionskolleg NRW (PK NRW) are continuing the English-language AI&ML colloquium. The open advanced seminar is aimed at PhD candidates, students, and staff who would like to engage with current scientific work in the fields of artificial intelligence (AI) and machine learning (ML) each semester. Under the direction of Prof. Dr. Markus Lange-Hegermann, the format offers a reliable framework for professional exchange – open in design and well received across disciplines.
PK NRW – Promoting doctoral studies
The AI&ML advanced seminar is a joint offering from inIT and the NRW Doctoral College (PK NRW), which has been establishing structures for doctoral programs at universities of applied sciences in North Rhine-Westphalia since 2020 and strengthening the next generation of researchers. The cross-university orientation creates additional professional perspectives and opportunities for exchange. For doctoral candidates, this joint program offers a valuable opportunity to further develop their scientific qualifications in a targeted manner.
Intensive exchange on scientific contributions
Each advanced seminar lasts three hours, allowing sufficient time for in-depth discussion of two scientific papers per session. A brief introduction to each paper is followed by a joint technical discussion, which regularly benefits from a variety of perspectives. The seminars are open to all interested parties and are occasionally supplemented by exciting contributions from Fraunhofer IOSB-INA and Phoenix Contact.
Focus of the semester
This semester, the advanced seminar will focus on two central topics in AI research. The first focus is on state space models, including work on long sequences, diagonal state space models, and the Mamba architecture. The second focus is on normalizing flows, with contributions on variational inference, real NVP, masked autoregressive flow, and Glow. Both topics offer the opportunity to jointly classify fundamental concepts and current developments.
Added value for your own research
“The advanced seminar enables a structured exchange on current AI methods,” says Prof. Dr. Markus Lange-Hegermann. “The clear focus helps to classify new approaches in a targeted manner and make them usable for one's own research.”