Firdaous Sekkay
Papers
2
Total Citations
8
H-Index
2
About
Firdaous Sekkay is a leading researcher at the intersection of human factors engineering, robotics, and sustainable manufacturing. Her work focuses on creating human-centric automation systems that prioritize worker well-being alongside operational efficiency. Sekkay’s major contributions include developing adaptive workload management frameworks for robotic assembly lines using fuzzy inference systems, as detailed in her 2024 paper (5 citations). She also pioneered WMSDsNet, a deep learning framework for real-time ergonomic risk prediction in human-robot collaboration during disassembly tasks (2025, 3 citations). This work is critical for advancing the circular economy by enabling safe, efficient component recovery. Sekkay’s research directly addresses the pressing need to reduce work-related musculoskeletal disorders (WMSDs) while optimizing human-robot collaboration. Her innovative integration of AI and ergonomics has garnered attention for its practical applications in manufacturing. By combining theoretical rigor with real-world relevance, Sekkay is shaping the future of sustainable, worker-centered automation. Her work stands as a vital resource for students and researchers exploring the nexus of robotics, human factors, and green manufacturing.
Research Focus
Key Achievements
Top Papers
- 1
- 2