Paula Chen Associate Professor

Paula Chen Associate Professor
Dr. Chen’s research focuses on Human-AI Interaction and Decision Science, centered on the intersection of technology, data, and human behavior. Her work integrates human factors, psychology, and behavioral data science to examine how humans interact with and make decisions within automated and AI-collaborative environments.
Her academic career includes tenure-track faculty positions at Florida State University (FSU) as an Assistant Professor and National Yang Ming Chiao Tung University (NYCU) as an Associate Professor. She has held visiting appointments at the University of Chicago and Michigan State University and served as a Senior Researcher at ACT, Inc. in the U.S., where she led several national-level assessment initiatives.
On the technical and practical front, she has led the development of automatic test assembly systems, focusing on User Interface (UI) design and interaction optimization. Furthermore, she has extensive experience in conducting large-scale behavioral intervention studies, utilizing machine learning (e.g., Random Forest) and advanced statistical methods on national-level longitudinal datasets (Add Health). With professional roots in the semiconductor (UMC, Etron) and financial sectors (Bank Sinopac), she specializes in translating behavioral insights into strategic technology management and resilient systems design.
EDUCATION
Her academic career includes tenure-track faculty positions at Florida State University (FSU) as an Assistant Professor and National Yang Ming Chiao Tung University (NYCU) as an Associate Professor. She has held visiting appointments at the University of Chicago and Michigan State University and served as a Senior Researcher at ACT, Inc. in the U.S., where she led several national-level assessment initiatives.
On the technical and practical front, she has led the development of automatic test assembly systems, focusing on User Interface (UI) design and interaction optimization. Furthermore, she has extensive experience in conducting large-scale behavioral intervention studies, utilizing machine learning (e.g., Random Forest) and advanced statistical methods on national-level longitudinal datasets (Add Health). With professional roots in the semiconductor (UMC, Etron) and financial sectors (Bank Sinopac), she specializes in translating behavioral insights into strategic technology management and resilient systems design.
EDUCATION
- Ph.D. in Quantitative Methods, The University of Texas at Austin
- M.A. in Statistics, The University of Texas at Austin
- M.S. in Human Factors Engineering, National Yang Ming Chiao Tung University
- B.S. in Psychology, National Taiwan University
Research Interests
- Human-AI Interaction and Decision Science
Course Taught
- Human-AI Interaction
- Big Data Analytics
- Multivariate Analysis
- High-Tech Product Management
- Business Negotiation and Conflict Management