Hendrik Woehrle

German Research Centre for Artificial Intelligence

Papers

Total Citations

H-Index

About

Hendrik Woehrle’s research lies at the intersection of brain-computer interfaces (BCIs), machine learning, and reconfigurable hardware, with a focus on moving neural signal processing from controlled labs into real-world robotic applications. His most cited work, “Online movement prediction in a robotic application scenario” (2013, 15 citations), tackles a critical gap: adapting electroencephalography (EEG)-based movement prediction systems to complex, multi-task environments where users face distractions—a key step toward practical BCI-driven robotics. He extended this with “Online Classifier Adaptation for the Detection of P300 Target Recognition Processes in a Complex Teleoperation Scenario” (2014, 7 citations), demonstrating adaptive algorithms that maintain accuracy in dynamic settings. Woehrle also contributed to hardware acceleration for machine learning (2015, 5 citations), exploring how reconfigurable systems can speed up signal processing pipelines. While his citation counts are modest, his work is notable for pioneering robust, real-time BCI systems that function outside idealized conditions—a challenge that remains central to the field. For students and researchers, Woehrle’s research underscores the importance of bridging algorithmic innovation with hardware and real-world constraints, offering a practical blueprint for deploying intelligent systems in noisy, unpredictable environments.