From 3rd to 5th June 2025 the 5th Helmholtz AI conference 2025 took place in Karlsruhe. The Helmholtz AI Conference is an annual event focusing on AI in science and research, featuring leading experts discussing advancements and their potential across various fields. Our senior researcher and CST group leader, Dr. Read more…
On May 13th, IML senior researcher and CST group leader Dr. Thiago Gouvêa delivered a keynote at the Digital Green Talents Spring School 2025 in Steinbach, sharing insights into interactive machine learning for biodiversity conservation and his team’s achievements in the XPRIZE Rainforest competition. The Spring School, part of the Read more…
As part of the series of lectures, the department of Applied Artificial Intelligence (AAI) at the University of Oldenburg has been displayed. Prof. Dr. Daniel Sonntag presented the AAI research areas to an interested audience at CORE Oldenburg on 12 March 2025. In his lecture about human-centred AI, Prof. Sonntag Read more…
The Lower Saxony press (Nordwest Zeitung/NWZ) and Oldenburg’s local Mox Journal published two interviews with Prof. Sonntag discussing generative and human-centered AI. As artificial intelligence becomes a widely discussed topic, the University of Oldenburg actively conducts research in this area. In these interviews, Prof. Sonntag elaborates on his research group’s Read more…
On 21 February 2025, the second industry symposium of the Department of Applied Artificial Intelligence (AAI) at the University of Oldenburg and of the DFKI research department Interactive Machine Learning (IML) took place at EWE Forum / Alte Fleiwa. More than thirty-five industry leaders and representatives from the regional economy Read more…
To celebrate the 50th anniversary of the University of Oldenburg, the Wechloy campus opened its doors for an “Entdeckertag” (discovery day) on May 31 and June 1st. As part of the Entdeckertag, the university presented its research and provided exciting insights into the many opportunities and possibilities at the Faculty Read more…
Explainable AI (XAI) has demonstrated its potential in deciphering discriminatory features in machine learning (ML) decision-making processes. Specifically, XAI’s feature attribution methods shed light on individual decisions made by ML models. However, despite their visual appeal, these attributions can be unfaithful. To ensure the faithfulness of feature attributions, it is Read more…
Medical image analysis encompasses two crucial research areas: disease grading and fine-grained lesion segmentation. Although disease grading often relies on fine-grained lesion segmentation, they are usually studied separately. Disease severity grading can be approached as a classification problem, utilizing image-level annotations to determine the severity of a medical condition. On Read more…