Hello! My name is Jiaming Qu (瞿佳明) and I am now a Ph.D. candidate in Information Science at School of Information and Library Science (SILS), UNC Chapel Hill. I am advised by Dr. Yue Wang and Dr. Jaime Arguello. Prior to my Ph.D. journey, I got my Master's Degree in Information Science at SILS.
My research lies at the intersection of Explainable Artificial Intelligence (XAI), Human-Computer Interaction (HCI) and Information Retrieval (IR) with two primary goals: (1) developing algorithms, visualizations, and interactive tools to help users understand AI systems; (2) conducting empirical studies to investigate how users interact with these tools. My PhD work can be grouped into three key themes chronologically:
- Explainable IR: I developed a ranking algorithm that explains the relevance of search results without compromising performance for biomedical literature search (SIGIR'20 and ECIR'21) and an ontology-based search system for neuroscience.
- Human-XAI Interaction: I developed XAI tools to explain machine learning predictions. I conducted a quantitative study to evaluate the effectiveness in assisting human decision-making (CIKM'21) and a qualitative study to investigate human's cognitive activities when interacting with XAI tools (CHIIR'23).
- Explaining Unintuitive Explanations: I developed computational tools to explain predictive but unintuitive words in text analysis (e.g., "problems" is predictive of positive Amazon reviews, or "Chicago" is predictive of deceptive hotel reviews). I conducted a mixed-method study to investigate how users interact with these tools (FAccT'24). Currently, I am doing my dissertation research on this topic.