Chao Wang

schoolHondabar_chart#2292 Global Rank

Total Papers

HCI Rank

#2292

Research Areas

Years Active

Recent Publications

ProjecTA: A Semi-Humanoid Robotic Teaching Assistant with In-Situ Projection for Guided Tours

Robotic teaching assistants (TAs) often use body-mounted screens to deliver content. In nomadic, walk-and-talk learning, such as tours in makerspaces, these screens can distract learners from real-world objects, increasing extraneous cognitive load. HCI research lacks empirical comparisons of potential alternatives, s…

DIS '252nd AuthorSocial Robot Interaction +1

“Teach Me About Objects!” – Experience-Driven Interaction for Teachable Robots

To adapt to specific places and people, robots must recognize objects, which are typically taught by users – a tedious process. Inspired by anecdotes of positive teaching experiences shared by educators, sports coaches, and animal trainers, we developed seven experience-driven ways to make teaching a robot more engagi…

CHI '254th AuthorHand Gesture Recognition +2

An Approach to Elicit Human-Understandable Robot Expressions to Support Human-Robot Interaction

Understanding the intentions of robots is essential for natural and seamless human-robot collaboration. Ensuring that robots have means for non-verbal communication is a basis for intuitive and implicit interaction. For this, we describe an approach to elicit and design human-understandable robot expressions. We outli…

CHI '254th AuthorHonorable MentionBrain-Computer Interface (BCI) & Neurofeedback +2

Developing and Validating the Perceived System Curiosity Scale (PSC): Measuring Users' Perceived Curiosity of Systems

Like humans, today's systems, such as robots and voice assistants, can express curiosity to learn and engage with their surroundings. While curiosity is a well-established human trait that enhances social connections and drives learning, no existing scales assess the perceived curiosity of systems. Thus, we introduce…

CHI '25CorrespondingHuman-LLM Collaboration +2

Investigating LLM-Driven Curiosity in Human-Robot Interaction

Integrating curious behavior traits into robots is essential for them to learn and adapt to new tasks over their lifetime and to enhance human-robot interaction. However, the effects of robots expressing curiosity on user perception, user interaction, and user experience in collaborative tasks are unclear. In this wor…

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