Urban development reduces green space, disrupts wildlife, and increases noise, diminishing everyday exposure to natural soundscapes and weakening people’s connection to nearby nature. We explore restoring urban natural soundscapes with personal Audio AR to help people reacquaint with everyday nature, and observe associations with perceived nature connectedness, eco-awareness (noticing both existing and missing greenery), and reflection. We present GreenAR, a ubiquitous location-aware system that composes spatial, visually-congruent biophony (birds, insects) from OpenStreetMap greenery around the listener. We conducted three in-situ studies: (1) an error-resilient sound placement evaluation under urban GPS conditions (n=16); (2) a campus study comparing with/without restoration (day/night) (n=16); and (3) a week-long field deployment in five countries (n=12). Participants reported higher nature connectedness with restoration, heightened awareness of vegetation and urban wildlife, attention to green deficits along routes, and occasional micro‑actions. Notably, one participant described a reversal from opposing to supporting urban greening policies, highlighting the potential of everyday ambient soundscapes to shape reflection on urban nature.

Environment designers in the entertainment industry create imaginative 2D and 3D scenes for games, films, and television, requiring both fine-grained control of specific details and consistent global coherence. Designers have increasingly integrated generative AI into their workflows, often relying on large language models (LLMs) to expand user prompts for text-to-image generation, then iteratively refining those prompts and applying inpainting. However, our formative study with 10 designers surfaced two key challenges: (1) the lengthy LLM-generated prompts make it difficult to understand and isolate the keywords that must be revised for specific visual elements; and (2) while inpainting supports localized edits, it can struggle with global consistency and correctness. Based on these insights, we present GenTune, an approach that enhances human--AI collaboration by clarifying how AI-generated prompts map to image content. Our GenTune system lets designers select any element in a generated image, trace it back to the corresponding prompt labels, and revise those labels to guide precise yet globally consistent image refinement. In a summative study with 20 designers, GenTune significantly improved prompt--image comprehension, refinement quality, and efficiency, and overall satisfaction (all $p < .01$) compared to current practice. A follow-up field study with two studios further demonstrated its effectiveness in real-world settings.

Research has shown that walking during meetings improves creativity, memory, attention, health, and happiness. While mobile technologies have freed users from having to be stationary during virtual meetings, mobile phones pose several usability challenges, such as reduced productivity due to small screens and safety concerns. In this paper, we present the first exploration of augmented reality (AR) interface design for virtual meetings in real-world walking conditions. We conducted design sessions in-situ with 16 user interface and AR designers using a 2x2 experimental design: meeting while walking in two levels of traffic conditions and with two types of meeting formats. Results show that the designed AR windows averaged 14.5 times in viewing size compared to the most popular smartphone screens. Also, Traffic Level significantly affected the size, opacity, and placement of windows, as well as the preference of anchoring modes, while Meeting Format significantly affected size and opacity. Furthermore, clustering analysis identified two groups of designs that can serve as initial reference designs for further customization and research.

Electrical Muscle Stimulation (EMS) has emerged as a key wearable haptic feedback technology capable of simulating a wide range of force feedback, such as the impact force of boxing punches, the weight of virtual objects, and the reaction force from pushing on a wall. To simulate these external forces, EMS stimulates the muscles that oppose (i.e. antagonistic to) the actual muscles that users activate, causing involuntary muscle contraction and haptic sensations that differ from real-world experiences. In this work, we propose Paired-EMS which simultaneously stimulates both the muscles that users activate and that prior EMS stimulates (i.e. antagonistic muscle pairs) to enhance the external force feedback experience. We first conducted a small formative study (n=8) to help design the stimulation intensity of muscle pairs, then conducted a user experience study to evaluate Paired-EMS vs. prior EMS approaches for both isometric and isotonic user actions. Study results (n=32) showed that Paired-EMS significantly improved realism, harmony, and entertainment (p<.05) with similar comfort (p>.36), and was overall preferred by 78% of participants (p<.01).

Interior design aims to create aesthetically pleasing and functional environments within an architectural space. For a simple room, the preliminary design exploration currently takes multiple meetings and days of work for interior designers to incorporate homeowners’ personal preferences through layout, furnishings, form, colors, and materials. We present RoomDreaming, a generative AI-based approach designed to facilitate preliminary interior design exploration. It empowers owners and designers to rapidly and efficiently iterate through a broad range of AI-generated, photo-realistic design alternatives, each uniquely tailored to fit actual space layouts and individual design preferences. We conducted a series of formative and summative studies with a total of 18 homeowners and 20 interior designers to help design, improve, and evaluate RoomDreaming. Owners reported that RoomDreaming effectively increased the breadth and depth of design exploration with higher efficiency and satisfaction. Designers reported that one hour of collaborative designing with RoomDreaming yielded results comparable to several days of traditional owner-designer meetings, plus days to weeks worth of designer work to develop and refine designs.

Real-world impact, such as hitting a tennis ball and a baseball, generates instantaneous, directional impact forces. However, current ungrounded force feedback technologies, such as air jets and propellers, can only generate directional impulses that are 10x-10,000x weaker. We present SpinShot, a flywheel-based device with a solenoid-actuated stopper capable of generating directional impulse of 22Nm in 1ms, which is more than 10x stronger than prior ungrounded directional technologies. Furthermore, we present a novel force design that reverses the flywheel immediately after the initial impact, to significantly increase the perceived magnitude. We conducted a series of two formative, perceptual studies (n=16, 18), followed by a summative user experience study (n=16) that compared SpinShot vs. moving mass (solenoid) and vs. air jets in a VR baseball hitting game. Results showed that SpinShot significantly improved realism, immersion, magnitude (p < .01) compared to both baselines, but significantly reduced comfort vs. air jets primarily due to the 2.9x device weight. Overall, SpinShot was preferred by 63-75% of the participants.

Mobile phones have enabled users to browse information in varying mobility contexts. For high-mobility settings such as walking, however, phones pose several usability challenges, particularly safety and limited screen sizes. While Augmented Reality (AR) has been proposed to address these issues, prior work has yet to investigate AR interface design in real-world walking conditions beyond text readability and notification design. This paper presents the first exploration of AR browsing interface design and extended usage while walking in the wild. We first conducted design sessions with 12 UI designers while walking in varied environments to design the window size, distance, opacity, anchor type, and placement for three categories of apps: text, video, and mixed content. Results show that traffic level significantly affects the designed window size, whereas content type significantly affects window size, distance, opacity, and vertical placement. To gain further insights from real-world usage, we conducted a multi-day observational study with 5 participants and observed that participants on average switched among window layouts every 3.3 minutes, for reasons such as safety and the level of extended visual attention.

First-Person View (FPV) drone is a recently developed category of drones designed for precision flying and for capturing exhilarating experiences that could not be captured before, such as navigating through tight indoor spaces and flying extremely close to subjects of interest. FPV viewing experiences, while exhilarating, typically have frequent rotations that can lead to visually induced discomfort. We present TurnAhead, which uses 3-DoF rotational haptic cues that correspond to camera rotations to improve the comfort, immersion, and enjoyment of FPV experiences. It uses headset-mounted air jets to provide ungrounded rotational forces and is the first device to support rotation around all 3 axes: yaw, pitch, and roll. We conducted a series of perception and formative studies to explore the design space of timing and intensity of haptic cues, followed by user experience evaluation, for a combined total of 44 participants (n=12, 8, 6, 18). Results showed that TurnAhead significantly improved overall comfort, immersion, and enjoyment, and was preferred by 89% of participants.