Lina Jiang

Nanning Normal University, State Grid Corporation of China (China)

Papers

Total Citations

H-Index

About

Lina Jiang is a researcher at the intersection of educational technology and artificial intelligence, with key contributions in human-robot interaction and computer vision. Her most cited work, "Impact of perceived ease of use and perceived usefulness of humanoid robots on students' intention to use" (2025, 18 citations), extends the Technology Acceptance Model to explore how students perceive and accept AI-driven educational tools, offering critical insights for designing more effective learning environments. In computer vision, Jiang developed the "ViT-Siamese Cascade Network for Transmission Image Deduplication" (2023, 2 citations), demonstrating technical expertise in applying transformer architectures to practical image processing challenges. Her research bridges the gap between human-centered design and cutting-edge AI, addressing both the psychological factors influencing technology adoption and the algorithmic innovations needed for real-world applications. With a growing citation footprint, Jiang's work is particularly valuable for educators, instructional designers, and AI engineers seeking to understand user acceptance of emerging technologies. Her dual focus on perception studies and deep learning positions her as a versatile contributor to the evolving landscape of AI in education and visual data management.