Sara Behdad
Papers
21
Total Citations
531
H-Index
11
About
Sara Behdad is a pioneering researcher at the forefront of human–robot collaboration (HRC) and sustainable manufacturing, with a particular focus on the disassembly of end-of-life (EOL) and electronic waste products. Her work addresses one of modern manufacturing's most pressing challenges: transforming the labor-intensive, uncertainty-laden process of product disassembly into an intelligent, efficient, and ergonomically sound operation. Behdad's most cited contribution, "Task Allocation and Planning for Product Disassembly with Human–Robot Collaboration" (2022, 161 citations), exemplifies her signature approach of combining optimization frameworks with real-world human factors. She has advanced the field through groundbreaking algorithms for disassembly sequence planning under uncertainty, human motion and intention prediction using transformer networks, and unsupervised activity recognition—enabling robots to anticipate and respond to human behavior in real time. Her comprehensive 2023 review paper has rapidly become a key reference for researchers entering the field. With a body of work spanning computer vision, deep learning, ergonomics, and remanufacturing systems, Behdad's research is shaping the future of circular economy practices and robotic automation, making her an essential voice in sustainable industrial engineering.
Research Focus
Key Achievements
Top Papers
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- 6Unsupervised Human Activity Recognition Learning for Disassembly Tasks36 citations · 2023
- 7Uncertainty-Assisted Image-Processing for Human-Robot Close Collaboration24 citations · 2022
- 8Disassembly Sequence Planning Considering Human-Robot Collaboration23 citations · 2020
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