Current 3D food printing systems impose engineering paradigms onto culinary practice, requiring users to design food as geometric models and slice them into discrete layers. This approach fundamentally misunderstands how humans create food – through continuous cooking actions like piping, filling, and spreading that encode centuries of embodied knowledge. We present SPICE (Smart Production of Individualized Culinary Essentials), a multi-material 3D printing system that reimagines food fabrication through action-oriented path planning derived from traditional cooking techniques. Rather than decomposing geometry into discontinuous layers and parallel toolpaths, SPICE generates continuous paths that directly encode cooking actions. Through three demonstration dishes, we show how preserving the gestural nature of cooking enables more intuitive control while enhancing precision over nutritional content. This work contributes to growing efforts in HCI to develop craft-informed fabrication systems, positioning food as a critical domain for exploring how computational tools can augment rather than replace embodied making practices.

Multimodal interactions can reduce cognitive load in demanding situations, such as driving [68, 69, 85]. While such interfaces are becoming more mainstream in vehicles, knowledge of situational and contextual factors which influence user preferences about these interactions is sparse. Through semi-structured interviews with 15 individuals, we take a scenario-specific look at perceptions, expectations, and concerns of voice, gesture, and multimodal interactions within vehicles. We presented participants with scenarios where cognitive load, social norms, and other situational factors vary greatly, such as heavy-traffic or multiple passengers. We found situational preferences of voice and gesture shifted greatly, and often contradicted broadly stated preferences. For example, users generally prefer touch, but use voice in complex traffic, and prefer gesture around other occupants to not interrupt conversations. Based on our findings, we share design considerations that can help interaction designers account for variations in user preference when designing modally flexible automotive interfaces.

As voice assistant usage continues to grow, their homogeneity becomes even more problematic with the UNESCO report, “I’d Blush if I could” showing that designing only feminine voice assistants encourages negative behavior, both with virtual assistants and with real people [3]. While masculine text-to-speech (TTS) voices exist, ones that cover the full range of gender presentations, such as non-binary or gender-ambiguous voices are largely missing. In this paper, we present a method of creating a non-binary TTS voice and an example voice, Sam, created with input from the non-binary and transgender communities. We have open-sourced the resulting voice, along with the process and data used to create it. Finally, we present results from a large-scale survey showing that non-binary individuals are more likely to prefer a non-binary voice assistant compared to cisgendered individuals and discuss differences across age and gender.

We introduce MechSense, 3D-printed rotary encoders that can be fabricated in one pass alongside rotational mechanisms, and report on their angular position, direction of rotation, and speed. MechSense encoders utilize capacitive sensing by integrating a floating capacitor into the rotating element and three capacitive sensor patches in the stationary part of the mechanism. Unlike existing rotary encoders, MechSense does not require manual assembly but can be seamlessly integrated during design and fabrication. Our MechSense editor allows users to integrate the encoder with a rotating mechanism and exports files for 3D-printing. We contribute a sensor topology and a computational model that can compensate for print deviations. Our technical evaluation shows that MechSense can detect the angular position (mean error: 1.4°) across multiple prints and rotations, different spacing between sensor patches, and different sizes of sensors. We demonstrate MechSense through three application examples on 3D-printed tools, tangible UIs, and gearboxes.

Today’s electronics are manufactured to provide stable functionality and fixed physical forms optimized for reliable operation over long periods and repeated use. However, even when applications don’t call for such robustness, the permanency of these electronics comes with environmental consequences. In this paper, we describe an alternative approach that utilizes sustainable transient electronics whose method of destruction is also key to their functionality. We create these electronics through three different methods: 1) by inkjet printing conductive silver traces on poly(vinyl alcohol) (PVA) substrates to create water-soluble sensors; 2) by mixing a conductive beeswax material configured as a meltable sensor; and 3) by fabricating edible electronics with 3D printed chocolate and culinary gold leaf. To enable practical applications of these devices, we implement a fully transient and sustainable chipless RF detection system.

The emergence of living organisms as entities in HCI presents an opportunity to collaborate with other beings through technology, align interspecies motives, and nurture greater empathy for the non-human. Plants are particularly interesting because of their natural ability to sense and respond to environmental stimuli and potential to enable more sustainable interaction design. However, due to the cross-disciplinary and emerging nature of this space, there is a need to identify overarching patterns and discern opportunities for unifying future research. This paper aims to systematically analyze existing Human-Plant Interaction (HPI) works by presenting a survey of projects across HCI, art/design, architecture, and bioengineering. We identify core design paradigms along the dimensions of HPI System Architecture, Plant I/O Coupling, Plant Interfacing and Manipulation Techniques, Application Context, and Scale. From these themes, we assemble a framework for HCI practitioners to approach HPI, and discuss opportunities and open questions for future exploration.

Previous gesture elicitation studies have found that user proposals are influenced by legacy bias which may inhibit users from proposing gestures that are most appropriate for an interaction. Increasing production during elicitation studies has shown promise moving users beyond legacy gestures. However, variety decreases as more symbols are produced. While several studies have used increased production since its introduction, little research has focused on understanding the effect on the proposed gesture quality, on why variety decreases, and on whether increased production should be limited. In this paper, we present a gesture elicitation study aimed at understanding the impact of increased production. We show that users refine the most promising gestures and that how long it takes to find promising gestures varies by participant. We also show that gestural refinements provide insight into the gestural features that matter for users to assign semantic meaning and discuss implications for training gesture classifiers.

As interest within the HCI community expands beyond urban settings, novel tools and devices are being developed to support more sustainable interactions with natural environments and inform conservation action. Yet little is known about the users of these devices, and how their requirements and priorities might affect the usability or operationalization of the devices in the real world. Using the ‘e-seed’, a biomimetic self-drilling interface as a ‘research probe’, we conducted a qualitative user study with 14 subject matter experts in areas like forestry and agriculture to understand the value and limits for devices and systems in ecological restoration and monitoring. We highlight unique challenges in existing ecological practices, opportunities for technological interventions, and the policies and economic constraints affecting the feasibility of such interventions. We present a set of critical design considerations for building and deploying novel devices in natural and semi-natural ecosystems and discuss implications for future research.

Sustainability is critical to our planet and thus our designs. Within HCI, there is a tension between the desire to create interactive electronic systems and sustainability. In this paper, we present the design of an interactive system comprising components that are entirely decomposable. We leverage the inherent material properties of natural materials, such as paper, leaf skeletons, and chitosan, along with silver nanowires to create a new system capable of being electrically controlled as a portable heater. This new decomposable system, capable of wirelessly heating to >70°C, is flexible, lightweight, low-cost, and reusable, and it maintains its functionality over long periods of heating and multiple power cycles. We detail its design and present a series of use cases, from enabling a novel resealable packaging system to acting as a catalyst for shape-changing designs and beyond. Finally, we highlight the important decomposable property of the interactive system when it meets end-of-life.

This work introduces “destaining” as an interactive component for the HCI community. While staining happens unintentionally (e.g., spilling coffee), destaining can be used as an intentional design tool that selectively degrades stains on textiles. We explore the design space using silver doped titanium dioxide (TiO2/Ag), stains and light as a set of design primitives for interactive systems. We then developed replicable and accessible fabrication and testing methods that enable HCI researchers and designers to upgrade various fabrics to self-destaining textiles. Next, we demonstrate a Self-deStaining textile interface with embedded Light Emitting Diodes (LEDs) and moisture sensors that activate cleaning. Lastly, we showcase how the textile can be used in everyday objects such as self-cleaning clothes, a patterning station for phone cases, and accessories that change patterns and colors based on the user’s experiences.

Machine learning approaches to auditory object recognition are traditionally based on engineered features such as those derived from the spectrum or cepstrum. More recently, end- to-end classification systems in image and auditory recognition systems have been developed to learn features jointly with classification and result in improved classification accuracy. In this paper, we propose a novel end-to-end deep neural network to map the raw waveform inputs to sound class labels. Our network includes an "inception nucleus" that optimizes the size of convolutional filters on the fly that results in reducing engineering efforts dramatically. Classification results compared favorably against current state-of-the-art approaches, besting them by 10.4 percentage points on the Ur- bansound8k dataset. Analyses of learned representations revealed that filters in the earlier hidden layers learned wavelet like transforms to extract features that were informative for classification.

Contemporary distributed enterprises present challenges in terms of demonstrating community activity awareness and coherence across individuals and teams in collaborating networks. Building with a Memory is an experiential media system that captures and represents human activity in a distributed workplace over time. The system senses and analyzes movement in two workspaces in a mixed-use building with the results rendered in an informative ambient display in the building entryway. We describe the design and development of the system, together with insights from two studies of the installation and promising future directions.

Building with a Memory is a subtle responsive intervention that aims to provide cohesion and community awareness through the use of light and color. The installation delivers thought-provoking information by capturing, analyzing and rendering real-time and archived human activity in a workplace setting. The installation senses movement in the space through an IR camera and computer vision techniques. Two custom lighting fixtures and a video monitor render the aggregated movements. The visually simple aesthetic of the piece aims to balance active engagement and passive contribution, providing a rewarding experience for both occasional passersby and regular users of the space. This paper describes the motivations and contributions of the installation, together with insights gained from an informal evaluation and directions for future explorations.

In this art submission we describe a collection of twelve multimedia art works that combine sound, images and animation. These works are the result of collaborative creative practice between media artists and students in the context of two high school Language Arts classes for non-Native English speakers. The works were created, in part, by the students physically acting out aspects of the composition within SMALLab, a mixed reality environment for multimodal composition. We call the works "Embodied Poetry" because of this physical action aspect. The title of the collection, Stratification, refers to the layers of meaning within human language. The theme of the collection is English Idioms and the works incorporate both literal and figurative meanings. Examples of idioms include "bringing home the bacon," "fighting a losing battle", and "cutting through red tape." These works were created in an everyday educational setting, with the goal of improving student learning. Nevertheless, they should be viewed as works of art. For us, the artistic contribution of this work includes the pieces themselves and also the guided creative process by which they were created. Thus, for the exhibit we will showcase the works themselves and a documentary describing the process.