Beril Yalcinkaya
Papers
2
Total Citations
7
H-Index
2
About
Beril Yalcinkaya is a pioneering researcher at the intersection of human-robot collaboration (HRC) and construction automation. Her work focuses on enabling safe, efficient teamwork between humans and heavy-duty robots in dynamic, unstructured environments—a critical challenge for real-world deployment. Yalcinkaya’s major contribution is the extension of the Fuzzy State-Long Short-Term Memory (FS-LSTM) architecture, a novel deep learning framework designed to handle the uncertainty and irregularity of sensor data in human activity recognition. This innovation directly addresses the gap between controlled lab settings and unpredictable construction sites. Her 2024 paper on this topic has already garnered 5 citations, signaling its impact on the field. In parallel, she established an on-site construction pilot for human–heavy-duty robot collaboration, a practical achievement that bridges theoretical advances with tangible industry application. Yalcinkaya’s work is laying the groundwork for a future where robots and humans work side-by-side in complex, real-world environments, making her a key voice in the evolution of collaborative robotics.
Research Focus
Key Achievements
Top Papers
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