Posters and Demonstrations

The Noise2Noise method allows for training machine learningbased denoisers with pairs of input and target images where both the input and target can be noisy. This removes the need for training with clean target images, which can be difficult to obtain. However, Noise2Noise training has a major limitation: nonlinear functions applied to the noisy targets will skew the results. This bias occurs because the nonlinearity makes the expected value of the noisy targets different from the clean target image. Since nonlinear functions are common in image processing, avoiding them limits the types of preprocessing that can be performed on the noisy targets. Our main insight is that certain nonlinear functions can be applied to the noisy targets without adding significant bias to the results. We develop a theoretical framework for analyzing the effects of these nonlinearities, and describe a class of nonlinear functions with minimal bias. We demonstrate our method on the denoising of high dynamic range (HDR) images produced by Monte Carlo rendering, where generating high-sample count reference images can be prohibitively expensive. Noise2Noise training can have trouble with HDR images, where the training process is overwhelmed by outliers and performs poorly. We consider a commonly used method of addressing these training issues: applying a nonlinear tone mapping function to the model output and target images to reduce their dynamic range. This method was previously thought to be incompatible with Noise2Noise training because of the nonlinearities involved. We show that certain combinations of loss functions and tone mapping functions can reduce the effect of outliers while introducing minimal bias. We apply our method to an existing machine learning-based Monte Carlo denoiser, where the original implementation was trained with high-sample count reference images. Our results approach those of the original implementation, but are produced using only noisy training data.

Noise2Noise, nonlinear functions, Jensen gap, Monte Carlo denoising, high dynamic range, tone mapping

https://0d2f0bc53ec40041bef323f40496ed3c.r2.cloudflarestorage.com/pcs/gi26c/gi26c-sub1004-i7.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=8c3c5bf11286f4699c7019eaeac51dfe%2F20260525%2Fenam%2Fs3%2Faws4_request&X-Amz-Date=20260525T175248Z&X-Amz-Expires=7200&X-Amz-SignedHeaders=host&X-Amz-Signature=7b8597fe88a323b92311d441e7780c1e8ffd510e21fdc41b62a8a75051e2559c

Coping flexibility, Mental wellbeing, Gamified LLM-based interaction, Personal informatics

https://0d2f0bc53ec40041bef323f40496ed3c.r2.cloudflarestorage.com/pcs/gi26c/gi26c-sub1005-i7.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=8c3c5bf11286f4699c7019eaeac51dfe%2F20260525%2Fenam%2Fs3%2Faws4_request&X-Amz-Date=20260525T175248Z&X-Amz-Expires=7200&X-Amz-SignedHeaders=host&X-Amz-Signature=f1a6ace1db51f0d99fe9b13ccfcd74a4839e6583ee06b111e752e843b14d8253

remote meetings, self-view, non-verbal cues, communication

Digital Audio Workstations (DAWs) have provided new forms of composition-based music-making. However, DAWs commonly do not support co-located social interactions and novice music-makers who are unfamiliar with digital music languages. Previous tabletbased applications aimed to support novice-music-makers through tangible interactions, yet a lack of work incorporates cross-device functionalities that can enhance collaboration between users. Snap- Tunes, a cross-device music-making application that allowed multiple users to compose music on individual devices, was developed to address this research gap. To further enhance collaboration and playfulness, we were motivated to develop embodied interactions that extend beyond touch. We update SnapTunes’ design space to include new gyroscopic-based features that more closely resemble the functionality of traditional DAWs. Future work includes developing a prototype of our updated design, and conducting a workshop with novice music-makers to test its overall user experience.

Cross-device interaction, Collaborative music production, Embodied Interactions, Touchscreen interface, Spatial rearrangement interaction, Digital Audio Workstation (DAW), Handheld devices, Personal devices

https://0d2f0bc53ec40041bef323f40496ed3c.r2.cloudflarestorage.com/pcs/gi26c/gi26c-sub1009-i7.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=8c3c5bf11286f4699c7019eaeac51dfe%2F20260525%2Fenam%2Fs3%2Faws4_request&X-Amz-Date=20260525T175248Z&X-Amz-Expires=7200&X-Amz-SignedHeaders=host&X-Amz-Signature=e7dc12de1bc57af3f45b846eca7a50f16f20f119abab2d067e06e95d38b6509e

haptic displays, hybrid actuation, immersive arts

https://0d2f0bc53ec40041bef323f40496ed3c.r2.cloudflarestorage.com/pcs/gi26c/gi26c-sub1010-i7.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=8c3c5bf11286f4699c7019eaeac51dfe%2F20260525%2Fenam%2Fs3%2Faws4_request&X-Amz-Date=20260525T175248Z&X-Amz-Expires=7200&X-Amz-SignedHeaders=host&X-Amz-Signature=e6b2d51f7d263bf4296c588ea7d69c2329424ae0b0f00c98d125c45f4d6fa8bd

As older adults increasingly prefer to age in place, their adult children often assume the role of informal caregivers. This dynamic creates a distinct tension between the adult child’s need for awareness and the older adult’s fundamental right to privacy. Traditional monitoring technologies, such as raw video feeds, often compromise the older adult’s autonomy. To address this challenge, this study explores the use of generative Arti!cial Intelligence (GenAI) to create abstract, privacy-preserving “visual summaries” of daily activities. We design a 14-day Experience Sampling Method (ESM) study with dyads consisting of older adults and their adult children. Through daily smartphone prompts, participants report their current context and evaluate pre-generated AI sketches, indicating their willingness to share or receive these images. Follow-up video interviews will further investigate participants’ boundary-setting behaviours. This research aims to quantify the privacy mismatch between generations and provide actionable design guidelines for applying visual abstraction in AI-mediated caregiving tools, ultimately supporting inter-generational connection while protecting user dignity.

older adults, health, generative AI, privacy, human-AI interaction, personal data

We present a subset of ndings from a semi-structured interview study with 11 Chinese Canadian young adults who had encountered misinformation shared by older family members in family group chats. Our early ndings focus on culturally relevant linguistic and hierarchical barriers, showing how misinformation correction in family chats is shaped not only by access to accurate information, but also by language, authority, and expectations of respect.

Misinformation Correction, Family Communication, Immigrant Family, Group Chats

As social robots become increasingly integrated into everyday environments, understanding whether humans extend social norms such as fairness to robotic agents is critical. This pilot study investigates whether varying levels of anthropomorphism influence decision-making in a zero-sum game. Using a modified Rock-Paper- Scissors game, we evaluated three robot configurations that varied in anthropomorphism in a within-subjects design. To operationalize vulnerability, the robot used easily exploitable strategies while displaying score-dependent emotional expressions of sadness or happiness. We examined whether participants would deviate from rational payoff maximization by intentionally losing rounds to reduce outcome inequality.

Human-Robot Interaction, Fairness, Anthropomorphism

Virtual interviews can create barriers for neurodiverse job seekers when performance depends on timing, social expectations, and unclear interaction cues. WebMoti-Employ is a real-time virtual interview support system that provides low-load feedback during mock virtual job interviews through AI-generated hints, gazebased emoticon feedback, timer feedback, and filler-word feedback. This research reports preliminary findings from a study with 14 neurodiverse job seekers who completed a virtual mock interview using the system. Results indicated good perceived usability on the System Usability Scale (M = 71.61, SD = 16.66) and low overall workload on NASA-TLX (M = 4.92, SD = 3.58), after reverse-scoring Performance. Participant feedback suggested that the system supported focus and response awareness, while also identifying issues regarding clarifying feedback meaning and reducing visual distraction. These findings may inform the design of virtual interview systems that can support neurodiverse job seekers during high-pressure hiring interactions.

Neurodiversity, Inclusive Design, Virtual Interviews, AI

https://0d2f0bc53ec40041bef323f40496ed3c.r2.cloudflarestorage.com/pcs/gi26c/gi26c-sub1019-i7.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=8c3c5bf11286f4699c7019eaeac51dfe%2F20260525%2Fenam%2Fs3%2Faws4_request&X-Amz-Date=20260525T175248Z&X-Amz-Expires=7200&X-Amz-SignedHeaders=host&X-Amz-Signature=bcc4dede58329baf9466eafa1dc674331b768ce75d2ab13309b1bd2cc34186d0

https://0d2f0bc53ec40041bef323f40496ed3c.r2.cloudflarestorage.com/pcs/gi26c/gi26c-sub1020-i7.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=8c3c5bf11286f4699c7019eaeac51dfe%2F20260525%2Fenam%2Fs3%2Faws4_request&X-Amz-Date=20260525T175248Z&X-Amz-Expires=7200&X-Amz-SignedHeaders=host&X-Amz-Signature=5566f469493434debcddaa7cdfecf229621cd3f1318c87f65dfdd495ed9dc18c

Haptic floor displays, miniature proxy, immersive arts

In this research we present GOV: Global Orbit Visualization tool, an interactive program that enables audiences to explore the vast number of objects (satellites, space stations, debris, etc) orbiting the Earth with a multi-modal interface. Audiences can switch between mouse-driven, text-driven, and fly-through interactive modes to tailor their experience and learn more about the multitude of objects in our skies. More generally, GOV demonstrates the feasibility of using gamified, multi-modal interfaces to explore large geospatial data for entertainment and education.

geospatial data interaction, multi modal interaction, space education

https://0d2f0bc53ec40041bef323f40496ed3c.r2.cloudflarestorage.com/pcs/gi26c/gi26c-sub1022-i7.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=8c3c5bf11286f4699c7019eaeac51dfe%2F20260525%2Fenam%2Fs3%2Faws4_request&X-Amz-Date=20260525T175248Z&X-Amz-Expires=7200&X-Amz-SignedHeaders=host&X-Amz-Signature=1172e57390fb4edbc503035d916fa3d84254b28dfa87eede02ca8bbf680fabf6

Older Adults, Digital Legacy, Death, Prototype, Interview Study

https://0d2f0bc53ec40041bef323f40496ed3c.r2.cloudflarestorage.com/pcs/gi26c/gi26c-sub1025-i7.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=8c3c5bf11286f4699c7019eaeac51dfe%2F20260525%2Fenam%2Fs3%2Faws4_request&X-Amz-Date=20260525T175248Z&X-Amz-Expires=7200&X-Amz-SignedHeaders=host&X-Amz-Signature=aaa2b3065ef2162209475d70c140d6fc809a33fa17eaa3b69ddeb03808e06a09

Human-Computer Interactions, Keyboard Shortcuts, Spaced Repetition, Spacing Effects

Employment-related SMS phishing (“smishing”) is increasing, yet users must judge message legitimacy through the limited cues provided by messaging interfaces. We conducted a screenshot-based study in which participants evaluated job-related messages across multiple messaging platforms, judged legitimacy, and reported the cues informing their decisions. Across platforms, participants relied on similar heuristic cues regardless of judgment correctness, suggesting challenges in cue interpretation rather than cue availability. We identify a pattern of interface-driven trust miscalibration, where platform-level trust perceptions shape message-level judgments, and implications for messaging and job-search systems.

SMS phishing, smishing, user behaviour, mobile security, employment scams, platform trust

As Generative AI becomes increasingly embedded in daily life, AI auditing that draws on diverse lived experiences is gaining recognition. Yet older adults—whose extensive life experiences offer distinct and often overlooked insight—remain underrepresented in this space. We present preliminary findings from an ongoing co-design study exploring how older adults participate in AI bias auditing.

Older adults, AI Bias, Algorithmic Bias, AI Auditing, Inclusive AI

This research investigates user-centered privacy notice design for humanoid social robots in domestic environments. Through a codesign study with 20 child–parent pairs, we identified distinct mental models of preferred privacy notices and control mechanisms across the two groups. Children favored social, embodied cues, whereas parents preferred persistent, explicit, and technically grounded signals. Our qualitative analysis also revealed a pronounced “surveillance anxiety,” particularly around robot mobility and autonomous movement within the home. Building on these findings, we derive five design implications: (1) the dominance of LED light as the preferred visual modality; (2) dialogue as a complementary channel that affords semantic clarity; (3) anthropomorphic placement that maps notice signals onto body regions matching the underlying sensor; (4) the emerging potential of pose and gesture as embodied state signals; and (5) age-dependent modality preferences that call for adaptive designs across developmental stages. Across parent participants, participants expressed a strong desire for meaningful control and active management of their personal data. We argue that privacy notices for domestic robots should move beyond screen-based terms of service toward embodied, multimodal cues paired with interactive approval mechanisms—supporting more transparent and accountable human–robot interaction in the home.

Human-Robot Interaction, Privacy Notice, Humanoid Robot, Domestic Social Robot

More than 2.2 billion people globally live with near or distance vision impairment, yet video game accessibility depends almost entirely on per-game effort: studios that do not invest in built-in features leave their titles permanently unreachable, and communitymade accessibility mods, though valuable, are confined to games that expose a modding API. We present Argus, a game-agnostic accessibility overlay that delivers real-time spoken narration for any video game without game-side modification or developer cooperation, operating solely on the rendered screen output. Argus captures the live game window, segments UI regions using open-vocabulary prompts (SAM 3), extracts text via OCR, and synthesises contextaware guidance through a local LLM and neural TTS engine—a pipeline that generalises across art styles without per-title training data. We demonstrate Argus on tutorial gameplay from Old School RuneScape and Minecraft, two visually and mechanically distinct titles, confirming that the same prompt vocabulary transfers across both rendering styles without reconfiguration.

video game accessibility, visual impairment, foundation model segmentation, SAM 3, OCR, large language models, text-to-speech, real-time overlay, game-agnostic

Extended Reality (XR), including AR and VR, is used in different areas such as entertainment, education, and healthcare, but this growing use raises concerns about user ergonomics and health. A main issue is head and neck posture, as long-term use of headmounted displays can cause strain, discomfort, and reduced performance. This study proposes a task-based framework for monitoring posture in sitting and standing positions and investigates how real-time visual feedback can improve posture. Using the headset’s built-in sensors, posture is monitored through measures of tilt, forward/backward leaning, and slouching. Based on previous studies, we have designed simple visual feedback (icons) to make users aware of and help them correct their non-neutral posture. Through a within-subject user study, we aim to examine how these visual cues influence users’ posture over time and whether they are effective.

AR/VR, Ergonomics, Head Posture

Live stream broadcasts on platforms like YouTube and Instagram are now widespread across news, politics, gaming, and entertainment. These events often attract large, global audiences. A key feature is real-time chat, enabling interaction between hosts and viewers. However, high activity can cause chats to scroll too quickly, reducing usability. Multilingual messages from global audiences can also hinder comprehension. To address these issues, we developed a custom live stream prototype built atop the YouTube platform. It retains YouTube’s default video and chat and adds an Artificial Intelligence (AI)-generated chat summary that updates regularly. The summary displays key discussion by fans in two formats, topics and paragraph. Google’s AI tool, Gemini, is used to translate and summarize live chat content.

Live stream, social media design, Artificial intelligence (AI), Machine translation, Korean popular music

https://0d2f0bc53ec40041bef323f40496ed3c.r2.cloudflarestorage.com/pcs/gi26c/gi26c-sub1039-i7.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=8c3c5bf11286f4699c7019eaeac51dfe%2F20260525%2Fenam%2Fs3%2Faws4_request&X-Amz-Date=20260525T175249Z&X-Amz-Expires=7200&X-Amz-SignedHeaders=host&X-Amz-Signature=227cc77c7a624b07aef2299e7659308dbb77d9d25e68b1c7409da3ab3e30385e

interaction techniques, haptic feedback

Web designers implement a variety of design strategies to maximize engagement and patronage from users. Visual choices in style, font, layout, colour as well as functional elements all play a role in a user’s initial impression of trustworthiness. At times, these very elements are exploited with deceptive patterns (DPs), to subtly manipulate user behaviour towards some user-detrimental end goal. Existing studies have looked at the impact of web design elements on users’ trust perceptions of websites, yet the effects of specifically deceptive pattern use on perceived trustworthiness have not been examined. While it may be intuitive to expect that increased frequency of deceptive designs in an interface would decrease perceived trust, it might not be the case for DPs given their subtle nature and mainstream prevalence. This study aims to examine the effects of DP number on user perceived trustworthiness of websites.

Website Design, Deceptive Patterns, Dark Patterns, Perceived Trustworthiness, User Trust, Trust Assessment

Point cloud upsampling methods are commonly evaluated using geometric similarity metrics such as Chamfer and Hausdorff distance, despite these objectives not necessarily reflecting whether added points meaningfully contribute to downstream reconstruction. This work investigates point cloud upsampling as a supportallocation problem through a support-aware implicit projection framework that emphasizes ownership specialization, reconstructionoriented support placement, and usefulness-aware evaluation rather than uniform density generation alone.

Point cloud, Up-sampling, Machine Learning, Implicit Fields

Virtual Reality (VR) helps users connect in a social environment, where they can immerse themselves in virtual spaces and engage in activities like chatting, dancing, and playing. This type of VR, also called Social VR (SVR), helps people who cannot interact in person due to geographical location or other limitations. However, the lack of physical sensations in SVR weakens its potential as an alternative to in-person interactions, due to a diminished sense of presence. We present our study designs to understand SVR users’ expectations regarding physical sensations and the social scenarios they engage in when using external haptic and thermal devices. Our goal is to design a novel interaction technique for SVR that combines these types of feedback to increase social presence.

Virtual Reality, Social Virtual Reality, Physical Sensations, Presence, Co-presence, Interactions, Socialization

https://0d2f0bc53ec40041bef323f40496ed3c.r2.cloudflarestorage.com/pcs/gi26c/gi26c-sub1043-i7.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=8c3c5bf11286f4699c7019eaeac51dfe%2F20260525%2Fenam%2Fs3%2Faws4_request&X-Amz-Date=20260525T175249Z&X-Amz-Expires=7200&X-Amz-SignedHeaders=host&X-Amz-Signature=7da6401bc71d04819e4fea4d8b4f96659d96d530d6f5c0d0a66b71d5faa73af1

Augmented Reality, Older Adults, Usability, Systematic Review

We present Beyond-FOV locomotion, a continuous VR navigation technique using above-neck unimanual gestures outside visual frustum of HMD-mounted cameras, supporting simultaneous navigation and object interaction without lower-limb movement, preserving natural headand gaze-based exploration across diverse postures, and improving accessibility for bare-hand users with lowerlimb disabilities. Evaluated as an imaginary interface using external motion tracking in a within-subjects study (N=16), Beyond-FOV matched or exceeded the performance of within-FOV bare-hand locomotion techniques, establishing it as a promising, accessible, and space-efficient method for bare-hand VR locomotion.

Virtual Reality, Continuous Locomotion, Motion Tracking, Unimanual Interaction, Beyond-field-of-view Interaction

Building multi-point haptic devices remains difficult because it requires expertise in programming, kinematics, hardware integration, and mechanical design. This creates a barrier for novice hapticians who want to prototype richer physical interactions but lack the multidisciplinary background needed to implement them. Existing frameworks such as CHAI3D provide strong runtime support for haptic rendering, but still require low-level C++ implementation. Existing authoring tools reduce programming effort for scene-level haptic content, but they generally assume the physical device already exists. This project explores a web-based authoring interface for modular multi-point haptic devices. The current prototype demonstrates a browser-based 3D environment for importing, arranging, inspecting, and viewing haptic components. While it is currently a visual proof of concept, it establishes the interface direction for future automated kinematics and CHAI3D-compatible code generation. This work introduces a web-based authoring workflow for modular multi-point haptic devices, moving early device design from low-level programming toward visual assembly and future automated kinematics.

haptics, multi-point haptics, authoring tools, CHAI3D, web-based interfaces, automated kinematics

Virtual reality (VR) systems often rely only on continuous visual rendering. This standard can create functional barriers and limit alternative interactive paradigms. We present a VR game designed to explore how an echolocation interface can be designed to deliver an accessible gaming experience for everyone. The game restricts continuous visual output and casts the player as a superhero navigating via spatial audio and a triggered radar action. This work prompts critical questions regarding the development of better echolocation interfaces to advance inclusive design in VR.

Virtual Reality, Accessibility, Echolocation, Spatial Audio, Inclusive Design, Blind and Low Vision, Cross-Modal Interaction

Bilingual Chinese–English writers code-switch constantly, and the dominant keyboard architecture (a manual mode toggle) breaks composition flow whenever a phrase needs to be typed in the other language. While modern decoders can already handle either language, the missing piece is an interaction layer that lets the writer move fluidly between them. We present an interactive prototype that presents six interaction modes drawn from a design space organized along four axes: visibility of inference, timing of intervention, user control, and adaptation target. The prototype contains example passages so that users can experience each interaction directly. We treat the demo as a design probe to spark conversation about how a future AI-assisted bilingual Input Method Editor (IME) should behave, with interaction patterns that travel beyond the bilingual case to other input methods that bridge keystrokes and intent.

Input method editor, bilingual text input, code-switching, mixedinitiative interaction, on-device language models, design probe

This interactive exhibit demonstrates LIDLbot, an all-in-one experiment platform designed to be used for psychological or linguistic experiments on conversational user interface interactions that require per-trial manipulations or measurements. LIDLbot features customizable modules and built-in voice agent and chatbot simulators to help researchers build streamlined experiments quickly. It offers benefits similar to Wizard-of-Oz setups, while not requiring live researcher administration of stimuli or responses. In this demo, we demonstrate the features of the platform, how to use it to set up experiments, and its use from a Participant’s perspective.

conversational agents, wizard of oz, voice interfaces, chat interfaces, psychology experiments

Interactive colour-space visualization tools are still fragmented between legacy desktop plugins and modern web demos that prioritize visual polish over data completeness. In practice, this leaves researchers without a robust, inspectable, full-resolution workflow for exploring colour-volume structure and interior occupancy. This paper presents a WebGPU technical demo that computes colourspace point clouds on the GPU, caches generated point buffers, and renders either native 1-pixel points or instanced circle splats for denser displays. The system supports full RGB lattice generation up to 2563 samples, image-driven unique-colour sets, multiple perceptual and cylindrical colour spaces, and interactive clip bounds for interior investigation. We describe the pipeline design, implementation tradeoffs, and how this approach addresses common limits in current tools.

colour spaces, WebGPU, point clouds, compute shaders, scientific visualization

We present a demonstration of an LLM-assisted qualitative analysis system that supports iterative, data-grounded interpretation. The system integrates model feedback directly into a documentcentered workflow, allowing researchers to write and refine interpretations while receiving structured evaluations grounded in reference datasets. Rather than generating analytical outputs, the system evaluates user-written text, highlighting both supported and potentially misleading interpretations. This design is intended to encourage critical engagement and position the model as a reflective assistant within the analytical process.

qualitative analysis, large language models, human-AI collaboration, interaction design, thematic analysis, iterative thematic inquiry

Many older adults wish to continue living in their own homes and communities. Adult children often provide essential social support for parents who are aging in place. In this work, we report preliminary findings of a field study in which we evaluated HomeLink, a home-based technology that encourage aging parents and adult children to provide social support and bond with one another. We report on their use of FidgeMagnet as a dedicated communication channel, its use to support boundary setting, and its role in supporting phatic communication.

Do, Not, Use, This, Code, Put, the, Correct, Terms, for, Your, Paper

Online banking has become essential for managing finances, yet many individuals encounter barriers when learning to use these systems. This includes older adults, some of whom have lower technical self-efficacy, which can lead to reliance on family or friends and often involves unsafe financial practices, such as the sharing of passwords or other sensitive information. Existing learning resources for online banking provide limited opportunities for building self-efficacy and lack support for hands-on practice on realistic interfaces. To address this, we developed BankBox, a sandbox environment that simulates the interfaces of Canadian banks and allows users to practice common online banking tasks such as e-transfers or bill payments. BankBox focuses on enabling users to learn independently, without risk, on an interface that closely matches their actual bank. This work introduces BankBox and presents its design and evaluation through user studies with older adults. Findings show that sandbox-based practice can support skill development and improve self-efficacy for online banking through repetition, task completion validation, and increased familiarity with the interface. We discuss how different learning modes affect user experience, and highlight implications for designing sandbox-based learning tools. The system is accessible through a standard web browser at https://bankbox.cs.umanitoba.ca/.

online banking, older adults, self-efficacy, practice, sandbox learning

Online furniture retail has a fundamental limitation: customers cannot perceive how a product fits within their own space before purchasing. Static images and two-dimensional planners fail to convey spatial scale and material texture, contributing to high return rates. We present AuraMR, a Mixed Reality (MR) system that transforms a furniture e-commerce catalog into a gesture-driven shopping experience. Using Unity3D and the Mixed Reality Toolkit (MRTK), AuraMR lets users browse a paginated three-dimensional catalog, search via a hand-tracked virtual keyboard, and place trueto-scale prefabs in their physical environment without controllers. The system sustains 78 FPS on Meta Quest 3, achieves 24 ms average search response, and scored a 96.1% pass rate across 51 test cases. A preliminary evaluation with 12 participants found that 91% rated the interaction intuitive and 75% expressed intent to use AuraMR for real purchases.

Mixed Reality, e-commerce, furniture visualization, Unity3D, MRTK, hand tracking, spatial computing, HCI

As haptics and tangible interaction are increasingly adopted, designers and collaborators face challenges in developing a shared understanding of physical modalities, materiality, and interaction possibilities. We present the Tickle Trunk, an open-source, hardware-only toolkit for rapid, playful exploration of haptic and tangible interactions. The toolkit consists of plug-and-play input and output widgets that can be combined in seconds without programming. Through modalities such as vibration, wind, pressure, temperature, light, and force feedback, the Tickle Trunk supports early-stage exploration, mutual learning, and brainstorming for mixed-expertise teams. This demo invites attendees to experience the toolkit firsthand, combine widgets, and imagine how diverse physical interactions could support applications in virtual reality, storytelling, accessibility, rehabilitation, education, and creative design.

haptics, brainstorming, open-source, hardware sketching

Colour plays an important role communicating information in the world around us. However, people with Colour Vision Deficiency (CVD) face challenges accessing this information because they perceive a reduced gamut of colours, resulting in difficulty differentiating and identifying certain colours. To help people with CVD, we propose a novel technique to convey invisible colour information through the use of a luminance displacement temporal pulse via video pass-through on a head-mounted display.

Colour Vision Deficiency, Colour Identification