Hi, I'm Kaixin Ji (吉凯昕)
PhD, RMIT University & ADM+S (ARC Centre of Excellence for Automated Decision-Making and Society)
Keywords: Human-centered AI for Behavior & Cognition
Thesis: Measuring Information Behaviors and Cognitive Bias Using Wearables[Link]
I study human cognition and behavior in information seeking using multimodal sensing and machine learning. My work examines how attention, memory, reasoning, and decision-making evolve over time, combining controlled user studies with neurophysiological and behavioral data (e.g., EEG, electrodermal activity (EDA), blood volume pulse (BVP), motion, and eye-tracking). During my PhD, I explored these questions through two main studies: Study 1 — I updated a theoretical model mapping how cognitive load and affective states evolve across the stages of information seeking. Through comprehensive signal analysis and machine learning, I showed that these mental and emotional shifts are reliably detectable from wearable data. I also released a public dataset, SenseSeek, to support future research. Study 2 — I investigated how cognitive dissonance — the discomfort that arises when information challenges our existing beliefs (confirmation bias) — manifests differently throughout information seeking with neurophysiological data and mixed-method analysis.
I am actively seeking a postdoctoral position in cognitive/affective computing, digital health, or related areas.