Brianna Posadas
Papers
1
Total Citations
5
H-Index
1
About
Brianna Posadas investigates the intersection of human cognition and computational systems, with a primary focus on trust factors in image analysis. Her most-cited work, "Human Trust Factors in Image Analysis" (2018), examines how user confidence and reliance shape the effectiveness of visual data interpretation, a critical concern in fields like medical imaging and autonomous systems. While her citation count of 5 reflects an emerging career, this foundational study offers early insights into the psychological and behavioral dimensions of human-AI collaboration. Posadas’s research contributes to understanding how trust influences decision-making in high-stakes environments, bridging gaps between human factors engineering and computer vision. Her work is particularly notable for addressing the often-overlooked human element in automated analysis, paving the way for more reliable and user-centered design in AI applications. As a developing scholar, Posadas’s focus on trust dynamics positions her at the forefront of a growing field, with potential implications for improving transparency and accountability in machine learning systems.
Research Focus
Key Achievements
Top Papers
- 1Human Trust Factors in Image Analysis5 citations · 2018