Evidence-Based Digital Design | AI · XR · HCI
I build evidence-based digital experiences at the intersection of AI, XR, and HCI.
Turning complex technology into interfaces people can understand and trust.
I hold a Ph.D. in Engineering and an M.S. in Digital Media, with extensive experience as an overall lead and end-to-end owner across product management, design direction, and development coordination. My work bridges rigorous research with practical digital design, focusing on making emerging technologies—AI, XR, and HCI—legible and trustworthy for real users.
As an adjunct professor, I have taught studio-based courses that emphasize prototype-driven learning, critique, and lightweight validation. I am seeking a tenure-track Assistant Professor position in Digital Design where I can advance evidence-based methods for designing AI and XR systems, while training the next generation of designers to work responsibly with complex, evolving technologies.
Trustworthy AI interfaces, XR interaction design, evidence-based methods for emerging tech
Studio-driven, prototype-centered courses with critique and lightweight validation focus
End-to-end leadership across PM, design, and development for digital products
A use-case-first information architecture redesign for a global medical technology product, increasing clarity and trust without formal testing (v1 hypothesis + validation plan).
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Three interconnected research clusters at the intersection of AI, XR, and evidence-based design
Designing explanation layers, uncertainty communication, and human-in-the-loop workflows that help users understand AI behavior, assess reliability, and maintain appropriate trust calibration.
Creating testable immersive interactions with measurable learning and decision outcomes. Exploring how spatial computing and mixed reality can support complex cognitive tasks through well-structured narrative and interaction design.
Developing rigorous yet pragmatic evaluation methods when perfect datasets are unavailable. Emphasizing explicit assumptions, proxy signals, and realistic measurement plans to build credible design knowledge in fast-moving technology domains.
Studio-driven, prototype-centered pedagogy with critique and evidence-based validation
My teaching centers on studio practice: students build functional prototypes, present them in structured critiques, and develop lightweight validation plans to test their design assumptions. I emphasize that even small-scale evidence—analytics, interviews, or focused usability tests—is more credible than intuition alone. Students learn to articulate what they know, what they assume, and how they would validate their work in the real world.
Hands-on course designing AI-augmented interfaces with focus on explainability, feedback loops, and user trust.
Immersive design projects exploring spatial interaction, narrative structure, and user testing in XR environments.
Evidence-based evaluation techniques adapted for fast-moving tech: proxy metrics, assumption mapping, rapid validation.
Designing data-driven interfaces that communicate complex information clearly and honestly.
Critical examination of AI ethics, bias, transparency, and accountability through design case studies and critique.
Every project requires:
Digital design projects demonstrating evidence-based methods, end-to-end ownership, and research-driven approaches
End-to-end redesign focused on clarity and trust for global audiences. Includes v1 hypothesis and validation plan.
Interface design for exposing AI reasoning, confidence scores, and uncertainty to support informed human oversight.
Mixed reality prototype for procedural learning with measurable comprehension and retention outcomes.
User-tested visualization system for exploring high-dimensional research data with clear provenance and uncertainty indicators.
Selected peer-reviewed publications, conference presentations, and invited talks will be listed here.
This section will include research papers on AI interface design, XR interaction patterns, and evidence-based evaluation methods for emerging technologies.
Comprehensive curriculum vitae including education, research, teaching, publications, and service.
CV PDF will be made available upon deployment.
Inquiries about research collaboration, teaching opportunities, or project discussions
wonju.hwangbo@example.edu
Available upon request
United States