About Me
I’m a curious and thoughtful researcher who cares deeply about how people experience the world — and I turn that understanding into user insights that strategically influence product directions.
My work focuses on helping teams move beyond usability improvements toward identifying new opportunities, unmet needs, and future directions grounded in real human experiences.
My story is featured on the People of Research Newsletter
My Journey
A cross-cultural UX researcher with living experience in Canada, Taiwan, and Germany, I bring a global perspective to understanding behavior, context, and meaning. My academic background includes:
Dual B.A. in English Literature,
Fu Jen Catholic University & University of Bayreuth
Taiwan & Germany
Master of Library and Information Studies,
University of British Columbia
Canada
Associate Certificate in UX,
British Columbia Institute of Technology
Canada
Shaped my cross-cultural perspective and strengthened my ability to interpret human behavior, narratives, and meaning across contexts.
I developed a strong foundation in research methods, information architecture, and human-centered design.
I gained professional development in UX and statistical analysis, enabling me to apply both qualitative and quantitative approaches in my research work.
Over the past 5+ years, I’ve worked across AI technology, consulting, gaming, healthcare, and human-computer interaction research, partnering with product teams, designers, and business stakeholders to inform product decisions and long-term strategy.
Professionally, I began in consulting in Taiwan, where I developed a foundation in business sense, structured problem-solving and stakeholder collaboration. I carry this skillset throughout my UX research career — from shaping go-to-market directions for emerging e-commerce services to contributing insights for AI products used at scale, my work consistently connects user needs with business impact.
I specialize in mixed-methods research, combining qualitative depth with quantitative signals to not only evaluate experiences, but also uncover new product possibilities. I’m particularly drawn to the early, ambiguous stages of product development, where the right questions — not just the right answers — can define the future direction of a product.
Across industries and geographies, my approach remains consistent: understand the bigger picture, ground decisions in evidence, and create clarity where there is uncertainty.
Beyond my professional work, I actively contribute to the UX community in Vancouver through mentorship, workshops, and knowledge sharing events. Apart from that, I’m especially interested in how emerging AI tools can augment research workflows and expand how we understand users.
At my core, I’m driven by curiosity, an openness to new perspectives, and a deep sensitivity to evolving user needs. I see UX researchers as anchors within product teams, grounding decisions in evidence while helping steer direction amid uncertainty. This perspective shapes how I approach my work and enables me to contribute to products in ways that are both thoughtful and impactful.
My Research Philosophy
Context Shapes Insight
My background in English Literature trained me to analyze meaning through context, which I bring into UX research. By understanding users' motivations, behaviors, and environments, I help product teams uncover insights that inform product strategy, not just usability fixes.
Align User Value with Business Strategy
I believe impactful research sits at the intersection of user needs and business goals. I translate user insights into strategic recommendations that inform product roadmaps, reveal new market opportunities, and support long-term product growth.
Lead Through Insight and Collaboration
I see research as a catalyst for better product decisions. By working closely with designers, product managers, and engineers, I help teams ask the right questions, build shared understanding, and act confidently on research insights.
My use of AI as a Research Copilot
I integrate AI tools into my research workflow as a copilot that supports (but does not replace) human judgment. AI can help speed up time-consuming tasks such as summarizing transcripts, identifying emerging patterns across large qualitative datasets, and writing Python code for quantitative survey data analysis. This allows research projects to move faster while still maintaining depth and rigor in analysis.
However, I think insight generation remains a human-led process. AI outputs often surface interesting directions, but meaningful insights come from interpreting those signals within the broader context of user behavior, business goals, and product constraints. By keeping a strong human-in-the-loop approach, I use AI to support the research process while ensuring the final insights remain thoughtful and grounded for product teams and business stakeholders.