Stefan Wildermann

Friedrich-Alexander-Universität Erlangen-Nürnberg

Papers

Total Citations

H-Index

About

Stefan Wildermann is a researcher whose work sits at the intersection of embedded systems, multi-core architectures, and real-time computing. His most significant contributions center on **invasive computing** — a paradigm for resource-aware parallel program execution on Multi-Processor Systems-on-a-Chip (MPSoCs). His most cited work, "Language and Compilation of Parallel Programs for \*-Predictable MPSoC Execution Using Invasive Computing" (2016, 17 citations), addresses one of the critical challenges in modern embedded systems: guaranteeing execution qualities such as timeliness, power consumption, and fault tolerance, rather than relying on best-effort behavior. This is particularly vital for safety-critical and real-time applications. Complementing this, his research on timing-predictable stream processing on MPSoCs tackles application interference and uncertainty in multi-core environments. Beyond parallel systems, Wildermann has also contributed to the field of computer vision, with work on self-organizing object tracking in smart cameras and 3D person tracking using particle filters. His research reflects a consistent drive to bridge the gap between theoretical computing guarantees and practical embedded system deployment, making his work valuable to engineers and researchers designing reliable, high-performance embedded platforms.