Seyed Omid Sajedi

University at Buffalo, State University of New York

Papers

Total Citations

H-Index

About

Seyed Omid Sajedi is a rising researcher in human-robot collaboration and intelligent manufacturing, with a focus on enhancing safety through advanced image processing and uncertainty quantification. His most-cited work, "Uncertainty-Assisted Image-Processing for Human-Robot Close Collaboration" (2022, 24 citations), addresses a critical challenge in Industry 4.0: ensuring worker safety in close-proximity human-robot interactions. By integrating deep learning models with uncertainty estimation, Sajedi enables more reliable human motion detection from 2D images, effectively transforming standard cameras into robust safety sensors. This approach mitigates the risks of false positives and negatives in dynamic environments, paving the way for safer, more flexible collaborative workspaces. His contributions bridge the gap between theoretical AI and practical industrial applications, offering scalable solutions that do not rely on expensive specialized hardware. Sajedi’s work is particularly notable for its emphasis on trustworthiness and real-time adaptability, making it highly relevant for researchers and engineers developing next-generation human-robot systems. With a growing citation record and a clear trajectory toward impactful, safety-critical innovations, Sajedi is establishing himself as a key voice in the future of human-centered automation.