Natalie Leesakul

Papers

Total Citations

150

H-Index

About

Natalie Leesakul is a leading researcher at the intersection of technology ethics, human-computer interaction, and sustainable innovation. Her work critically examines the societal implications of emerging technologies, with a primary focus on responsible robotics, digital manufacturing, and privacy-preserving AI. Leesakul’s most influential contribution, "Workplace 4.0: Exploring the Implications of Technology Adoption in Digital Manufacturing on a Sustainable Workforce" (2022, 105 citations), provides a foundational framework for understanding how Industry 4.0 technologies impact worker well-being, job security, and skill development—a key resource for policymakers and industry leaders navigating digital transformation. She also advanced the field of domestic robotics with "Responsible domestic robotics: exploring ethical implications of robots in the home" (2019, 37 citations), which outlines critical design principles to prevent user harm and societal rejection. More recently, her work on "Facial identity protection using deep learning technologies: an application in affective computing" (2022, 8 citations) tackles the urgent challenge of data privacy in emotion recognition systems, proposing novel methods to decouple identity from affect. Through these contributions, Leesakul has established herself as a vital voice in shaping ethically grounded, human-centered technology development for the future.