Members of IISLab had the valuable opportunity to participate in the 2025 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2025), held in Trondheim, Norway, from March 17 to 20. They presented their latest research findings at a conference that brought together leading researchers and practitioners in artificial intelligence, machine learning, and computational intelligence.
The team led by Prof. Peter Drotár presented the paper titled "A Deep Ensemble Learning Approach for Imbalanced Data in Bankruptcy Prediction", co-authored by Peter Gnip, Róbert Kanász, and Martin Zoričak. Their research addresses the persistent challenge of class imbalance in bankruptcy prediction by introducing a leveraged TabNet architecture, contributing to the development of more accurate and reliable financial risk assessment models.
Additionally, the team led by Prof. Juraj Gazda presented the paper "Split Computing in Autonomous Mobility for Efficient Semantic Segmentation using Transformers", co-authored by Róbert Rauch and Chris Uličný. Their study explores innovative applications of split computing and transformer models to significantly enhance the efficiency of autonomous mobility systems. We are proud to announce that their work was nominated for the Best Paper Award at the conference.
IEEE SSCI 2025 provided an outstanding platform for academic exchange, networking, and fostering future collaborations. We extend our sincere thanks to the organizers for hosting a well-structured and inspiring event, and we look forward to participating in the next edition!