Daniel Lohmann
Papers
1
Total Citations
6
H-Index
1
About
Daniel Lohmann is a leading researcher in the field of embedded systems and operating systems, with a particular focus on resource-aware programming and self-adaptive computing. His work addresses the critical challenge of optimizing software performance on modern multiprocessor system-on-chip (MPSoC) architectures, where limited resources demand intelligent, adaptive behavior. Lohmann’s most-cited paper, "Self-adaptive corner detection on MPSoC through resource-aware programming" (2015), exemplifies his approach by demonstrating how applications can dynamically adjust their computational strategies—such as image processing algorithms—to meet varying resource constraints without sacrificing accuracy. This contribution has been recognized with over 6 citations, highlighting its influence in the embedded systems community. Lohmann’s research bridges the gap between hardware and software, enabling more efficient and resilient systems for real-time and safety-critical applications. His work is particularly notable for its practical impact, offering concrete methodologies for developers to build adaptive software that can respond to changing environmental conditions. For students and researchers, Lohmann’s insights provide a foundational understanding of how to design systems that are both powerful and resource-efficient.
Research Focus
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Top Papers
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