人机交互
Social robots are increasingly deployed in clinical settings to support the well-being of children, where effective support must be personalized to each child. Personalization, choosing the robot action best suited to each child, can be…
As autonomous vehicles progress toward fully driverless mobility, a critical question emerges: who understands and responds to passengers when the human driver is absent? Existing autonomous driving systems primarily optimize predefined…
Deceptive patterns are tactics used to manipulate users into performing unintended actions. Today, many of these deceptive patterns are implemented in mobile apps targeting diverse age groups. In this paper, we employ a heuristic-based…
People respond to artificial intelligence chatbots (AICs) in highly variable ways. In this paper, we adapt Bronfenbrenner's theory into a heuristic framework for understanding this variation. The framework places the human user at the…
The ability to automatically infer analytic intent from user interaction histories could enable interactive AI systems to proactively assist users during exploratory data analysis. In this paper, we examine whether provenance logs --…
Research-based digital health interventions are often presented as potential solutions for extending health care in the real world. Yet the vast majority of these interventions fails to move beyond controlled studies. Existing frameworks…
Classic models cast information seeking as iterative foraging: formulate a keyword query, scan results, reformulate, gather across sources, synthesize. We ask what happens when a conversational assistant is inserted into that episode.…
Low-dimensional projections support interactive visual analysis of high-dimensional data embeddings, but their structure often does not align with analyst-defined semantic relationships. Recent LLM-augmented semantic steering methods…
Developing conceptual understanding in engineering requires learners to connect spatial reasoning with abstract representations, yet lecture-based instruction often provides limited support for this process. Interactive learning…
Adaptive systems increasingly operate in environments characterized by persistent non-stationarity, where patterns reorganize rather than merely vary. While existing approaches such as online learning, continual learning, and adaptive…
Creating 3D assets for virtual reality requires modeling expertise, which restricts the authorship of immersive experiences. Existing generative AI tools rely on unconstrained, command-driven prompting, lacking the conversational…
Generative AI is increasingly used for everyday health guidance, yet its clinical appropriateness in chronic disease contexts remains poorly understood. This paper presents a two-part mixed-methods study on \revise{Type 2 Diabetes Mellitus…
Large language model personas are increasingly used to approximate diverse users during early-stage visualization design, but it remains unclear whether persona-conditioned outputs reflect stable personality effects or artifacts of model…
Virtual reality (VR) systems can enable convenient hand-based interactions across diverse work scenarios. However, mid-air gestures lack tactile feedback and a physical reference surface to support the hand. This absence of haptic grounding…
In today's data-driven world, students often struggle with interpreting visualisations due to limited visualisation literacy. Data comics have emerged as a promising medium to enhance engagement and understanding, but their educational…
Human personality inventories are increasingly used to characterize large language models (LLMs), compare systems, and inform downstream governance claims. Yet, these inventories were developed and validated for humans, and it remains…
Human-AI teaming has received increasing attention in the literature. However, the range of studies conducted in multiple domains make it difficult to understand what types of teams are being studied, and in what ways are they…
Americans' warmth toward members of the opposing political party has fallen sharply over the past three decades -- yet meaningful cross-partisan contact remains scarce, in part because people actively avoid it. Across five preregistered…
Exploring similar nodes in attributed networks represents a key challenge in data mining. While recent representation learning methods embed networks into low-dimensional vectors, they often implicitly assume a uniform and continuous…
Young people consistently say they want authentic self-expression, less judgment, and more interpersonal trust on social media, yet they rarely manage to engage that way. My dissertation argues that the obstacle is normative rather than…