Preisträger*innen – UNIVIE Forschungspreise für Studierende 2025/2026

Iterative solvers for large, sparse linear systems are widely used on powerful supercomputers. When solving very large problems, communication poses a significant bottleneck, which has prompted the development of communication-avoiding algorithms. We investigate how these algorithms can be combined with novel randomization strategies and introduce a new approach that achieves up to four times the performance of the current state-of-the-art on a modern supercomputer.

Deep clustering uses neural networks to automatically find patterns and group similar data together without needing labeled examples. In both works, we propose to improve existing deep clustering models using periodic resets of the network weights during training. We demonstrate that established centroid-based deep clustering methods achieve substantially higher accuracy when trained with our novel algorithms that overcome the performance plateaus and enhance the training with pseudo-labels. Our approaches use weight resets to avoid early over-commitment to initial cluster assignments and iteratively refine pre-trained models using their own clustering assignments. In experiments across multiple benchmark datasets, we observe consistent performance gains that deliver foundational contributions in deep clustering.

The study centers on the development and testing of “Codonia,” an educational game that employs challenge-based learning and interactive feedback. Through qualitative and quantitative analysis, findings reveal that gamification significantly increases motivation and confidence, supporting problem-solving and logical thinking. The results suggest that well-structured educational games can complement or even surpass traditional teaching methods. By showcasing how digital learning environments foster experimentation and sustained engagement, this work contributes to ongoing discussions about innovative tools for programming education.

This research examines key aspects of educational game design, including game mechanics, virtual environments, and scientific simulations. By leveraging real-world astronomical data, the game provides an accurate representation of celestial bodies, planetary atmospheres, and orbital mechanics. Additionally, the integration of narrative-driven missions ensures that learning is embedded within engaging gameplay rather than being separate from it. The study also addresses challenges in balancing scientific accuracy with user engagement, optimizing the game's interface for effective information delivery, and evaluating its educational impact through user testing. The results demonstrate the potential of serious games to enhance STEM education by making complex scientific concepts more accessible and enjoyable.