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From UX to AI: A Student's Journey in Human-Centered Research
Siwan Kim
Hometown:
Seoul, South Korea
Education:
Ph.D. in Data Science, University of Virginia
M.S. in Information Systems (UX Major) 2022, Yonsei University
B.S. in Content Convergence 2020, Ewha Womans University
Meet Siwan Kim, a Ph.D. in Data Science student at the University of Virginia (UVA), whose journey spans user experience design, information systems, and human-centered computing. Originally from Seoul, South Korea, Kim brings industry experience as a UX (User Experience) designer at LG CNS and an academic foundation grounded in design and technology.
Now pursuing doctoral research, she is exploring how human-centered design, AI, and data science intersect to shape more meaningful and responsible technologies. In this Q&A, Kim shares what sparked her interest in data science, why she chose UVA’s interdisciplinary Ph.D. program, and how she hopes to bridge theory and practice through research that puts people at the center of data-driven innovation.
Q: When and how did you become interested in data science?
Over the past three and a half years, I worked as a UX designer at LG CNS in Seoul. While facing the rapid changes in the IT industry, I realized that data plays a critical role in detecting latent user needs. This led me to become fascinated with data science, so I can better understand user behavior and expectations. I believe that multiple perspectives surrounding data science are more important than ever as we continue in the AI era.
Q: Choosing a doctoral program is a big decision. Why did you choose UVA's Ph.D. in Data Science?
I studied in a mixed academic field during my undergraduate and graduate school, rather than being purely rooted in technology. I wanted to join an interdisciplinary Ph.D. program where I could both learn and excel, while also leveraging my strength in human-centered design. With distinguished faculty from varied backgrounds, a well-designed curriculum paired with the energy of a vibrant community, I was happy to find and join such a program.
Q: What areas of research interest you and why?
My research interest is practice-based research on human-AI interaction and developing data-driven frameworks to address real-world problems. Numerous AI-powered tools are emerging, along with research into AI technology, but there is still much to explore regarding AI’s application to real-world contexts and the enhanced utilization of user data. I will explore the intersection of human-centered design, AI, and data science through my research.
Q: What do you hope to do with your data science degree?
With my data science degree, I aspire to transmute from a UX designer solving assigned problems to a researcher defining impactful ones. I believe that advancing data-driven research can bridge the gap between theory and practice, and my aim is to be an integral part of the bridge through my degree, research, and ultimate career trajectory.
Q: What advice would you give to prospective students considering a Ph.D. in Data Science? What do you wish you had known before starting?
My greatest advice is to develop your unique perspective through broad experiences. When I was in graduate school, I focused primarily on academic life and internships. However, I wish I had devoted more time to international conferences and collaborative research. So, I recommend having more research experience, which will be the source and fuel for admission and a future research life.
Q: What are your initial impressions of the school, faculty, and other students? What are you most excited about, and what challenges do you anticipate?
From the admission process, I felt the school was transparent, considerate, and attentive. I feel that this is an environment where collaboration is valued over competition. I’m both excited and anxious about acquiring new knowledge and skills in data science, but I know challenges are an integral part of life, and ultimately, I welcome them. Now, I'm going through one of the biggest changes in my life, and I look forward to embarking on this new journey in data science with my human-centered design perspective.
