Christopher Greene

Binghamton University, Stevens Institute of Technology

Papers

Total Citations

H-Index

About

Christopher Greene is a researcher at the forefront of human-robot collaboration, focusing on the critical intersection of industrial robotics, human factors, and cognitive AI. His work is distinguished by a pragmatic approach to integrating robots into human-centered environments, from manufacturing floors to healthcare settings. Greene’s most influential paper, "Collaborative Robot Selection Using Analytical Hierarchical Process" (2019, 8 citations), provides a much-needed structured methodology for choosing cobots—a key contribution for industries lacking standard selection procedures. He further explores human-robot dynamics in "Humanoid Robot: Application and Influence" (2018, 6 citations), examining how age, gender, and robot design affect user acceptance. Most recently, his 2024 paper (2 citations) offers a respectful critique of autonomous robotics in healthcare, arguing for human-centered, cognitively inspired AI to bridge the gap between technological optimism and practical reality. By grounding his research in cognitive science and neuroscience, Greene is shaping a future where robots are not just tools, but thoughtful collaborators designed with human needs at their core.