Project title: TAIHU: User Research for a Conversational AI Knowledge Discovery Platform Context: A multi-year research project at National Taiwan University to build a conversational AI platform that helps humanities scholars explore primary-source databases. My role: As a research assistant, I drafted the interview guide, conducted the year-2 interviews, analyzed interview data to develop personas, supported journey mapping through qualitative coding, and analyzed survey data quantitatively. Methods: Interviews, qualitative coding, personas, journey mapping, survey analysis. Scale: Interviews with 10+ scholars; a year-2 usability study with 130+ participants (system trial, A/B testing of model responses, surveys, interviews); a year-3 two-week longitudinal study with 30+ participants. Outcome:The journey map charted scholars' research workflow in six stages, from scoping a topic to writing a paper, and captured their actions, needs, pains, and time demand at each stage. It showed that collecting and reading primary materials and formulating research questions are the most time-intensive stages. It also translated scholars' pains, such as overwhelming and scattered materials and incomplete keyword searches, into concrete opportunities for AI support, including filtering sources, summarizing materials, and identifying gaps in current research.