Kaixin Ji

PhD Candidate, RMIT University

Kaixin’s research focuses on using physiological signals to quantify confirmation bias during information retrieval activities.

In today’s information-filled world, we rely heavily on information retrieval systems like Google to get the information we need. However, these systems often use algorithms and elements that prioritise catching our attention over presenting balanced viewpoints. This can lead to misinformation, manipulation, and the reinforcement of existing beliefs. Confirmation Bias, where people tend to favour information that aligns with their current beliefs, plays a significant role in this process. Studies show confirmation bias influences information reception, especially in health and politics. People tend to spend more time on information that supports their views and may even read opposing views with a critical attitude to disagree rather than accept. Existing solutions, such as training our brains or optimising search engines, have limitations. Technical solutions that prevent biased thinking and provide awareness are crucial. Kaixin’s research proposes using physiological data, such as skin conductance, heart rate, and gaze movement, to objectively measure and quantify confirmation bias during information retrieval activities. Her approach aims to overcome the limitations of subjective surveys and qualitative research. The main research questions focus on whether physiological data can discriminate information processing activities and detect as well as measure the level of confirmation bias in the information retrieval process.

Kaixin is a scholarship recipient of the ARC Centre for Automated Decision-Making and Society (ADM+S) is supervised by Prof. Falk Scholer, Dr. Damiano Spina, Prof. Flora Salim and Dr. Danula Hettiachchi.

Visit Kaixin’s personal website to learn more about her research.



  1. Examining the Impact of Uncontrolled Variables on Physiological Signals in User Studies for Information Processing Activities
    Kaixin JiDamiano SpinaDanula HettiachchiFlora D Salim, and Falk Scholer
    In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’23), 2023
  2. Towards Detecting Tonic Information Processing Activities with Physiological Data
    Kaixin JiDamiano SpinaDanula HettiachchiFalk Scholer, and Flora D. Salim
    In Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing (UbiComp/ISWC ’23 Adjunct), 2023