With a background in Design and Computer Science, I create research-backed frameworks that bridge the gap between complex theory and implementation. My work equips organizations with methods to navigate the unknown, empowering teams to achieve collective progress and innovation at scale.
Currently at Google, investigating 'what if' and 'what is'
For speaking engagements: info [at] paulaconn.com
My research explores the interplay of humans and high-performance systems. Specifically I'm interested in:
As an applied scientist, I work on a range of topics—from hardware thermal ergonomics to interactive machine learning—with a core focus on ensuring that the human experience remains at the heart of technical advancement. My recent publications include:
To balance computational performance with thermal comfort, this study explores a consolidated hotspot architecture at the top center of a tablet. The findings underscore the importance of thermal mapping and contextual sensing, with direct applications for software throttling thresholds of coated aluminum enclosures.
Building on research that emphasizes the need for specialized datasets and model training tools, our study uses a scaffolded approach to understand the ideal model training and voice recording process. This study offers important insights on creating more effective conversational systems by emphasizing the need to integrate interactive machine learning into training strategies.
This paper expands upon existing frameworks and contributes to an empirical understanding of smartphone accessibility. Specifically, this work highlights the need to shift current design practices to better serve the accessibility community.