In data-driven systems, integrating disparate data sources becomes challenging when incoming data does not conform to the system’s specifications. Despite advances in automated schema matching systems, data integration tasks involving complex semantic interrelationships still require users to manually identify and define transformations between datasets, which can be cognitively demanding and time-consuming. We present DataSpeck, an end-to-end system that automates the conversion of disparate data sources to fit any pre-existing data specification. DataSpeck employs an AI-driven human-in-the-loop design, using LLMs to analyze semantic relationships and generate step-by-step transformation pipelines autonomously, while only requesting user attention to resolve semantic ambiguities. In our technical evaluation, DataSpeck successfully automated ~86% of varied data transformations while generating interpretable strategies with confidence scores and targeted clarification requests. In a user study (N=12), participants completed data conversion tasks ~53% faster with significantly reduced cognitive load using DataSpeck compared to Microsoft Excel with Copilot.

As VR expands into public spaces, new challenges emerge around spontaneous interactions between bystanders and unfamiliar VR users. While current VR systems often prioritize user awareness of their physical surroundings, they overlook the social dynamics affecting nearby bystanders. We conducted a deception-based study (N=80) examining how interface availability influences bystanders’ comfort, confidence, and hesitation when interrupting VR users. We compared traditional static interruption interfaces (e.g., button on screen) with a proactive proxy that actively approached bystanders upon detecting interruption intent. Static interfaces, due to insufficient cueing, frequently caused bystander discomfort, leading to hesitant physical interruptions or complete communication avoidance. In contrast, the proactive proxy implicitly conveyed social permission, significantly enhancing bystanders’ comfort and confidence. Our findings provide empirical insights into how bystanders assess availability and initiate interruptions with unfamiliar VR users in shared spaces, offering design implications for VR systems that support bystander agency and comfort during these interactions.

Virtual Reality (VR) offers portable and flexible workspaces. However, enabling efficient and comfortable interactions without external input devices remains challenging. We propose leveraging redirected input to enable comfortable and touch-like interaction for quick and intuitive control. Our design study revealed that while touch interaction performs well with direct input, its performance degrades significantly under input redirection. In contrast, using pinch improves redirected input by providing self-haptic feedback and reducing input dimensionality, thereby compensating for spatial discrepancies. Based on these findings, we introduce Redirected Pinch, a bare-hand interaction technique that combines input redirection with pinch confirmation. It creates a virtual plane at waist height, remapping hand movements on the plane to a vertical window, with pinch gestures used for confirmation. A user study demonstrated that Redirected Pinch achieves a strong balance of accuracy, efficiency, comfort, and sense of agency across fundamental interactions.

Tasks that involve locating objects and then moving hands to those specific locations, such as using touchscreens or grabbing objects on a desk, are challenging for the visually impaired. Over the years, audio guidance and haptic feedback have been a staple in hand navigation based assistive technologies. However, these methods require the user to interpret the generated directional cues and then manually perform the hand motions. In this paper, we present automated hand-based spatial guidance to bridge the gap between guidance and execution, allowing visually impaired users to move their hands between two points automatically, without any manual effort. We implement this concept through FingerRover, an on-finger miniature robot that carries the user’s finger to target points. We demonstrate the potential applications that can benefit from automated hand-based spatial guidance. Our user study shows the potential of our technique in improving the interaction capabilities of people with visual impairments.

Wearable devices allow quick and convenient interactions for controlling mobile computers. However, these interactions are often device-dependent, and users cannot control devices in a way they are familiar with if they do not wear the same wearable device. This paper proposes a new method, UnifiedSense, to enable device-dependent gestures even when the device that detects such gestures is missing by utilizing sensors on other wearable devices. UnifiedSense achieves this without explicit gesture training for different devices, by training its recognition model while users naturally perform gestures. The recognizer uses the gestures detected on the primary device (i.e., a device that reliably detects gestures) as labels for training samples and collects sensor data from all other available devices on the user. We conducted a technical evaluation with data collected from 15 participants with four types of wearable devices. It showed that UnifiedSense could correctly recognize 5 gestures (5 gestures × 5 configurations) with an accuracy of 90.9% (SD = 1.9%) without the primary device present.

QR codes have been used as an inexpensive means to connect users to digital platforms such as websites and mobile applications. However, despite their ubiquity, QR codes are limited in purpose and can only redirect users to the URL contained within it, thereby making their use heavily network dependent which can be unsuitable for use in ephemeral scenarios and areas with limited connectivity. In this paper, we introduce Frappé, a framework capable of deploying ultra lightweight UIs to mobile devices directly through QR codes, without requiring any network connectivity. This is achieved by decomposing the UI into metadata and storing it inside the QR code, while offloading the UI functionality to API calls. We also introduce enFrappé, a WYSIWYG tool for building Frappé UIs. We demonstrate the lightweight nature of our framework through a technical evaluation, whereas the usability of our UI builder tool is demonstrated through a user study.