Presenter: Celeste Seah
Title: Rememo
Abstract:
Rememo is an interactive tool designed to support reminiscence therapy through AI-generated imagery tailored to older adults’ lived experiences. Developed in collaboration with therapists and care staff, the tool facilitates meaningful conversations by generating personalized visuals based on culturally relevant prompts. Through iterative prototyping and field testing in local care facilities, Rememo explores how AI technologies can be meaningfully integrated into existing care workflows, balancing technical capabilities with therapists’ needs and clients’ preferences. The project highlights design considerations around personalization, usability, and trust when deploying AI in sensitive, human-centered contexts such as eldercare.
Presenter: HAN BO
Title: Slip Casting as a Machine for Making Textured Ceramic Interfaces
Abstract:
Ceramics provide a rich domain for exploring craft, fabrication, and diverse material textures that enhance tangible interaction. In this work, we explored slip-casting, a traditional ceramic technique where liquid clay is poured into a porous plaster mold that absorbs water from the slip to form a clay body. We adapted this process into an approach we called Resist Slip-Casting. By selectively masking the mold’s surface with stickers to vary its water absorption rate, our approach enables makers to create ceramic objects with intricate textured surfaces, while also allowing the customization of a single mold for different outcomes. In this paper, we detail the resist slip-casting process and demonstrate its application by crafting a range of tangible interfaces with customizable visual symbols, tactile features, and decorative elements. We further discuss our approach within the broader conversation in HCI on fabrication machines that promote creative collaboration between humans, materials, and tools.
This demo will showcase some ceramic pieces that were fabricated with the developed resist slip-casting technique.
Presenter: Lasitha Amarasinghe
Title: AiGet - proactive AI assistant for AR smart glasses
Abstract:
AiGet is a proactive AI assistant, integrated with AR smart glasses, designed to seamlessly embed informal learning into low-demand daily activities such as casual walking and shopping. By analyzing real-time user gaze patterns, environmental context, and user profiles, AiGet leverages large language models to deliver personalized, context-aware knowledge with minimal disruption to primary tasks.
In demonstrations, users wear HoloLens2 AR smart glasses and explore their surroundings. When AiGet detects interesting and novel information within the environment, it informs the user through visual and auditory feedback. Users can then interact with AiGet by asking questions to enhance their knowledge.
Presenter: Han Meng
Title: Interactive Visual Analytics of Causality in Psychological Constructs