WeavePrint: A Generative Method for Woven-like Additive Manufacturing Based on Parametric Weave StructuresThis paper presents WeavePrint, a parametric and multi-material additive manufacturing method for woven-like structures. By fusing traditional weaving logic with computational generation, WeavePrint overcomes limitations in pattern programmability, mechanical tunability, and build size. A parametric generator creates plain, twill, satin, and image-based jacquard patterns, while supporting curved-surface mapping and continuous vertical roll-to-roll printing for scalable production. Systematic tensile and compression tests quantify how overlap length, filament width, and multi-material combinations influence inter-layer adhesion and global mechanics. We define four motion primitives: bending, twisting, curved extension-contraction, and hinged extension-contraction, implemented through straight, diagonal, and curved weaves to produce predictable deformations. Demonstrations in wearable supports, robotic components, and rehabilitation devices highlight its broad potential in human-computer interaction. By unifying parametric modeling with multi-material continuous fabrication, WeavePrint provides a scalable route to programmable, anisotropic, and dynamically responsive interactive fabrics.2026JCJiacheng Cao et al.Zhejiang UniversityShape-Changing Interfaces & Soft Robotic MaterialsShape-Changing Materials & 4D PrintingCustomizable & Personalized ObjectsCHI
PoemPalette: Facilitating Poetry Creative Exploration and Foundational Understanding through the Ideorealm Alignment of Paintings and PoemsThe “Ideorealm Alignment of Paintings and Poems (IA-PP)” theory rooted in Chinese classical aesthetics offers a perspective for exploring poetry’s deep connotations. This study presents PoemPalette, a novel IA-PP creative-exploration tool that integrates generative AI to guide poetry enthusiasts in actively constructing an ideorealm for the poetic painting they envision, informed by a formative study with six experts. We extract the core symbols of poetry, transform them into Scene Graph (SG), and generate images for users to freely compose, enabling IA-PP creative exploration. The system incorporates Large Language Model (LLM) agents to enhance the foundational understanding of poetry. In a controlled experiment on Chinese poetry and Japanese haiku with 60 participants, we analyze which interaction mechanisms most contribute to foundational understanding and creative outcomes, compared with both AI and non-AI baselines. Situated within East Asian poetry traditions, this study introduces cultural theories to guide the design of AI co-creation tools, using a graph-based interface of interpretable intermediate representations.2026YZYing Zhang et al.Zhejiang UniversityGenerative AI (Text, Image, Music, Video)Human-LLM CollaborationCreative Collaboration & Feedback SystemsCHI
Seeing Eye to Eye: Enabling Cognitive Alignment Through Shared First-Person Perspective in Human–AI CollaborationDespite advances in multimodal AI, current vision-based assistants often remain inefficient in collaborative tasks. We identify two key gulfs: a communication gulf, where users must translate rich parallel intentions into verbal commands due to the channel mismatch , and an understanding gulf, where AI struggles to interpret subtle embodied cues. To address these, we propose Eye2Eye, a framework that leverages first-person perspective as a channel for human-AI cognitive alignment. It integrates three components: (1) joint attention coordination for fluid focus alignment, (2) revisable memory to maintain evolving common ground, and (3) reflective feedback allowing users to clarify and refine AI's understanding. We implement this framework in an AR prototype and evaluate it through a user study and a post-hoc pipeline evaluation. Results show that Eye2Eye significantly reduces task completion time and interaction load while increasing trust, demonstrating its components work in concert to improve collaboration.2026ZTZhuyu Teng et al.Zhejiang UniversityHuman-LLM CollaborationAR Navigation & Context AwarenessImmersion & Presence ResearchCHI
ImmersiProtor: A Collaborative Mixed-Prototype Tool Integrating Spatial Augmented Reality and Component-layered GenerationConceptual design is a critical stage in product development, involving multidisciplinary collaboration based on prototypes. This paper proposes a novel prototype paradigm combining generative artificial intelligence (GAI) and spatial augmented reality (SAR), leveraging SAR's expressive potential and GAI's creative potential for co-design. We first conducted a formative study with designers to explore how these technologies could be effectively integrated. Based on our findings, we introduce ImmersiProtor, a prototype tool integrating multi-view SAR and component-layered GAI. ImmersiProtor enables design team members to freely create and modify physical prototypes while automatically generating multi-view, high-fidelity renderings projected onto prototype surfaces, facilitating immersive communication and intuitive evaluation. It also introduces a component-layered generation and collaboration mode with personal and shared team resources, allowing individual exploration without interference while supporting concept integration, evaluation, and iteration. We implemented ImmersiProtor as a web-based application with an SAR design space and conducted a user study to verify its usability. Results highlighted ImmersiProtor's strengths in enhancing intuition, promoting collaboration, and strengthening GAI controllability. We also explored mixed interaction's effect on design and discuss best practices for the HCI community.2026HZHongbo ZHANG et al.Zhejiang UniversityAR Navigation & Context AwarenessGenerative AI (Text, Image, Music, Video)Prototyping & User TestingCHI
3DInkGen: Extending Traditional Ink-Painting Artistry with Generative 3D Creation for NovicesInk painting, renowned for its aesthetics and historical significance, plays a vital role in global art. 3D ink art extends this tradition into spatial forms, enriching digital media like animation and games. However, existing methods for 3D ink creation demand expertise in both 3D modeling and ink aesthetics, limiting novice participation and 3D ink application.Through formative research with four experts, including ink painting artists and 3D designers, we summarize the core challenge: how to preserve the expressive pattern of ink paintings while constructing 3D structures.To tackle this challenge, we introduce 3DInkGen, a system that transforms 2D ink elements into editable 3D compositions. 3DInkGen follows a four-stage workflow: element extraction, form generation, 3D reconstruction, and style transfer.A user study with sixteen novices showed 3DInkGen lowers technical barriers and enables intuitive 3D composition. The four experts believe novice-created works captured the artistic style of ink painting while maintain 3D structure of elements.2026JZJiesi Zhang et al.School of Software Technology3D Modeling & AnimationDigital Art Installations & Interactive PerformanceInteractive Narrative & Immersive StorytellingCHI
KiriInflate: Fabricating Cross-Scale Inflatables with Large-Magnitude Contraction and Tunable Stretchability for Tangible InteractionWe present KiriInflate, a rapid, precise, and accessible fabrication method for creating stretchable inflatables with Kirigami structures. These inflatables, fabricated at multiple scales (from fingernail-sized to body-sized), exhibit rapid, large contraction upon inflation up to 83.5% and provide tunable stretchability. Our fabrication process leverages the electrostatic adhesion of plastic films and an off-the-shelf laser cutter to simultaneously cut and fuse the edges of inflatables, achieving ultra-narrow seals (< 0.125 mm). Our structural design enables versatile 3D morphing upon inflation and tunable stretch behavior, with experimental studies offering design guidelines for key geometric parameters. A series of applications, including an eyelid assistive device, a multi-mode game handle, a dynamic elbow brace, and breathable lamps, highlight its potential for diverse interaction in HCI.2025YYYue Yang et al.Shape-Changing Interfaces & Soft Robotic MaterialsShape-Changing Materials & 4D PrintingUIST
"This is My Fault", Really? Understanding Blind and Low-Vision People’s Perception of Hallucination in Large Vision Language ModelsVisual question-answering (VQA) tools powered by large visual language models (LVLMs) are used to assist blind and low-vision (BLV) individuals in overcoming visual challenges, raising concerns about hallucinations and associated risks. Existing literature overlooks the variations of hallucinations across distinct usage scenarios and types in the context of VQA for BLV people, resulting in limited understanding of their perceptions and insufficient guidance for targeted mitigation strategies. By analyzing 3,467 real-world VQA cases from BLV users, we developed a manifestation-scenario-based dual-dimensional hallucination typology, uncovering eight scenarios and five types of hallucinations. Through interviews with 16 BLV users, we examined their awareness levels, detection strategies, mental models of hallucinations, and their tolerance of associated risks, identifying key gaps between their perceptions and real situations. By designing with 12 BLV users, we uncovered their expectations for hallucination-mitigating solutions, including enhanced information provision, transparency in processing, verification strategies, and feedback mechanisms.2025YTYilin Tang et al.Voice AccessibilityExplainable AI (XAI)AI Ethics, Fairness & AccountabilityUIST
SCENIC: A Location-based System to Foster Cognitive Development in Children During Car RidesCar-riding is common for children in modern life, and given the repetitive nature of daily commutes, they often feel bored, which in turn leads them to rely on electronic devices for entertainment. Meanwhile, the rich and rapidly changing scenery outside the car naturally attracts children’s curiosity, providing abundant resources for cognitive development. Our formative study reveals that parents' support during car rides is often fleeting, as accompanying adults may struggle to consistently provide effective guidance to nurture children's innate curiosity. Therefore, we propose SCENIC, an interactive system that guides children aged 6-11 to better perceive the external environment through location-based cognitive development strategies. Specifically, we built upon the experiential approaches used by parents, culminating in the formulation of six cognitive development strategies integrated into SCENIC. Additionally, considering the repetitive nature of car commutes, SCENIC incorporates features of dynamic POI selection and journey gallery generation to improve children's engagement. We evaluated the quality of SCENIC's generated content (N=21) and conducted an in-situ user evaluation involving seven families and ten children. Study findings suggest that SCENIC can enhance the car riding experience for children and help them better perceive the external environment through cognitive development strategies.2025LCLiuqing Chen et al.Motion Sickness & Passenger ExperienceMicromobility (E-bike, E-scooter) InteractionUniversal & Inclusive DesignUIST
Touch-n-Curl: Designing and Constructing Skeletal Form through 3D Printing Flattened Zipper AssemblyIn the realm of digital fabrication, skeletal structures offer lightweight, cost-effective solutions for art installation, rapid fabrication, and large-scale construction. However, existing 3D printing methods for skeletal structures often require support structures, resulting in prolonged print time and excessive material consumption. This paper presents Touch-n-Curl, a design and construction system for rapidly prototyping 3D skeletal curved structures, covering scales from millimeters to meters, by printing 2D zipper assemblies with interlocking mechanisms using conventional 3D printers. This design process is made possible by a computational method that unrolls a 3D model into a 2D branch assembly while minimizing branch intersections, making the fabrication process both efficient and robust. A parametric design tool is developed to support this inverse design workflow, instantly generating 2D zippers and offering a preview of the 3D skeletal assembly. To ensure users can effectively utilize the system, we implement methods such as edge disjoining and tree rectification to accommodate closed mesh imports in addition to opened trees at a wide range of complexity measured by curvature and torsion. The result of this integrated and accessible workflow is evaluated in fabrication speed, mechanical strength, and shape-matching accuracy, and its versatility is showcased through a series of demonstrations.2025DPDeying Pan et al.Desktop 3D Printing & Personal FabricationCircuit Making & Hardware PrototypingUIST
An Exploratory Study on How AI Awareness Impacts Human-AI Design CollaborationThe collaborative design process is intrinsically complicated and dynamic, and researchers have long been exploring how to enhance efficiency in this process. As Artificial Intelligence (AI) technology evolves, it has been widely used as a design tool and exhibited the potential as a design collaborator. Nevertheless, problems concerning how designers should communicate with AI in collaborative design remain unsolved. To address this research gap, we referred to how designers communicate fluently in human-human design collaboration, and found awareness to be an important ability for facilitating communication by understanding their collaborators and current situation. However, previous research mainly studied and supported human awareness, the possible impact AI awareness would bring to the human-AI collaborative design process, and the way to realize AI awareness remain unknown. In this study, we explored how AI awareness will impact human-AI collaboration through a Wizard-of-Oz experiment. Both quantitative and qualitative results supported that enabling AI to have awareness can enhance the communication fluidity between human and AI, thus enhancing collaboration efficiency. We further discussed the results and concluded design implications for future human-AI collaborative design systems.2025ZCZhuoyi Cheng et al.Human-LLM CollaborationAI-Assisted Decision-Making & AutomationIUI
I-Card: A Generative AI-Supported Intelligent Design Method Card DeckA design method card deck helps designers understand and provoke thinking by presenting each method in a simple format and allow designers to switch between methods seamlessly by maintaining the same simple format across the deck. However, recent observations have shown designers hesitate to use a card deck due to the lack of support, while other tools have provided identified support with generative AI. Through a formative study, we identified the specific support designers need when applying the design method cards and intentions in integrating generative AI. Accordingly, we developed the intelligent design method card deck, I-Card, which integrates generative AI to provide applicable design methods, design knowledge and data support, and interactive and dynamic support. A user study demonstrates that I-Card improved the design efficiency and applicability by offering personalized guidance, enhanced decision-making with comprehensive data generation and provided more design inspiration via interactive support.2025LCLiuqing Chen et al.Zhejiang University, College of Computer Science and TechnologyGenerative AI (Text, Image, Music, Video)Prototyping & User TestingCHI
FusionProtor: A Mixed-Prototype Tool for Component-level Physical-to-Virtual 3D Transition and SimulationDeveloping and simulating 3D prototypes is crucial in product conceptual design for ideation and presentation. Traditional methods often keep physical and virtual prototypes separate, leading to a disjointed prototype workflow. In addition, acquiring high-fidelity prototypes is time-consuming and resource-intensive, distracting designers from creative exploration. Recent advancements in generative artificial intelligence (GAI) and extended reality (XR) provided new solutions for rapid prototype transition and mixed simulation. We conducted a formative study to understand current challenges in the traditional prototype process and explore how to effectively utilize GAI and XR ability in prototype. Then we introduced FusionProtor, a mixed-prototype tool for component-level 3D prototype transition and simulation. We proposed a step-by-step generation pipeline in FusionProtor, effectively transiting 3D prototypes from physical to virtual and low- to high-fidelity for rapid ideation and iteration. We also innovated a component-level 3D creation method and applied it in XR environment for the mixed-prototype presentation and interaction. We conducted technical and user experiments to verify FusionProtor’s usability in supporting diverse designs. Our results verified that it achieved a seamless workflow between physical and virtual domains, enhancing efficiency and promoting ideation. We also explored the effect of mixed interaction on design and critically discussed its best practices for HCI community.2025HZHongbo ZHANG et al.Zhejiang University3D Modeling & AnimationCircuit Making & Hardware PrototypingCHI
Voice by the Non-sighted: Practices and Challenges of Audiobook Voice Actors with Blind and Low Vision in China Auditory sense is the primary channel for people with blind and low vision (BLV) to access information. This paper aims to understand the productization of individual voices of BLV voice actors in the audiobook industry. We conducted online semi-interviews with the BLV voice actors in China (N = 13) and gained insights into the workflow through offline observations. Interviews indicate that the ability to match job requirements, social benefits, and accessible support are key factors that draw BLV people into this field. They acquire vocal techniques, actively showcase their voices, and adapt their career paths as needed. Social support is crucial for their continued employment, as well as disclosing their BLV identities as appropriate. Observations reveal that BLV people utilize text processing tools, Screen Reader(SR) speed control, and keyboard shortcuts to transform an invisible script into a coherent and emotionally nuanced voice recording. We investigate how BLV people harness their potential through intensive voice acting while listening to SR, and proficient keyboard skills for software access.2025SCShi Chen et al.International Design Institute, Zhejiang UniversityVoice User Interface (VUI) DesignVisual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)CHI
Ink Restorer: Virtual Restoration of Ancient Chinese Paintings Inheriting Traditional Restoration ProcessesThe restoration of ancient Chinese paintings plays an essential role in protection and inheritance of Asian culture. A traditional restoration process consists of four stages: Xi (washing), Jie (separating), Bu (mending), and Quan (completing). However, it is difficult for the public to experience this process due to high professional requirement and time consumption. We conduct a questionnaire survey and interview experts in our formative study. The questionnaire result shows the public express strong interest in virtual restoration. Experts believe virtual restoration is an experience valuable for the public. We introduce Ink-Restorer, a tool designed for experiencing virtual restoration for ancient paintings. Its design follows the traditional restoration process, and it adopts image segmentation and generation techniques to simplify detailed restoration for users. We recruit 60 users to evaluate Ink-Restorer and invite experts to evaluate restoration results. Ink-Restorer significantly improves user experience, cultural understanding, and restoration quality.2025YZYing Zhang et al.School of Software Technology, Zhejiang UniversityMuseum & Cultural Heritage DigitizationFood Culture & Food InteractionCHI
CoExploreDS: Framing and Advancing Collaborative Design Space Exploration Between Human and AIIn product design, effective design space exploration (DSE) is crucial for generating high-quality design ideas, requiring designers to possess broad knowledge and balance various constraints. As large-scale models thrive, AI has become an indispensable design collaborator by providing cross-domain knowledge and assistance with complex reasoning. To facilitate collaborative DSE between designers and AI, we frame and advance the design process through the problem-solution co-evolution model and design reasoning methods. A formative study was conducted to identify key strategies for the implementation. Then we developed CoExploreDS, a system that formalizes problems and solutions emerging in the human-AI collaborative design space into nodes. Using four reasoning methods, this system dynamically generates suggestions based on the ongoing design process. User studies confirmed that CoExploreDS significantly improves design quality and the human-AI collaboration experience.2025PCPei Chen et al.Zhejiang UniversityHuman-LLM CollaborationComputational Methods in HCICHI
IEDS: Exploring an Intelli-Embodied Design Space Combining Designer, AR, and GAI to Support Industrial Conceptual DesignConceptual design is an important stage in industrial product development, influenced by the design space and materials available to designers. Advancements in human-computer interaction (HCI) and artificial intelligence (AI) technologies have broadened these aspects considerably. On the one hand, augmented reality (AR) technologies merge physical and virtual representations to enhance intuitive interaction and embodied cognition. On the other hand, generative artificial intelligence (GAI) serves as a novel design material, boosting creativity and productivity. Inspired by these technological strides, we proposed an Intelli-Embodied Design Space (IEDS), which integrates designers, AR, and GAI to support industrial conceptual design by combining embodied interaction with generative variability. Within IEDS, designers can interact with the physical prototypes intuitively, while GAI refines these into virtual forms that can be embedded in the physical world through AR technology. In this study, we established the theoretical framework and interaction modes of IEDS through literature reviews and expert interviews. Subsequently, we designed and implemented three GAI+AR tools, GAI + Head-mounted Display (HMD), GAI + Handheld Display (HHD), and GAI + Spatial Augmented Reality (SAR), based on three AR approaches in IEDS to practically examine the benefits and challenges of these interaction modes across industrial conceptual design tasks. We discussed IEDS's influence on industrial conceptual design and released its application guidelines to the HCI community.2025HZHongbo ZHANG et al.Zhejiang UniversityAR Navigation & Context AwarenessGenerative AI (Text, Image, Music, Video)Prototyping & User TestingCHI
TH-Wood: Developing Thermo-Hygro-Coordinating Driven Wood Actuators to Enhance Human-Nature InteractionWood has become increasingly applied in shape-changing interfaces for its eco-friendly and smart responsive properties, while its applications face challenges as it remains primarily driven by humidity. We propose TH-Wood, a biodegradable actuator system composed of wood veneer and microbial polymers, driven by both temperature and humidity, and capable of functioning in complex outdoor environments. This dual-factor-driven approach enhances the sensing and response channels, allowing for more sophisticated coordinating control methods. To assist in designing and utilizing the system more effectively, we developed a structure library inspired by dynamic plant forms, conducted extensive technical evaluations, created an educational platform accessible to users, and provided a design tool for deformation adjustments and behavior previews. Finally, several ecological applications demonstrate the potential of TH-Wood to significantly enhance human interaction with natural environments and expand the boundaries of human-nature relationships.2025GWGuanyun Wang et al.Zhejiang UniversityShape-Changing Interfaces & Soft Robotic MaterialsHuman-Nature Relationships (More-than-Human Design)CHI
X-Hair: 3D Printing Hair-like Structures with Multi-form, Multi-property and Multi-functionIn this paper, we present X-Hair, a method that enables 3D-printed hair with various forms, properties, and functions. We developed a two-step suspend printing strategy to fabricate hair-like structures in different forms (e.g. fluff, bristle, barb) by adjusting parameters including Extrusion Length Ratio and Total Length. Moreover, a design tool is also established for users to customize hair-like structures with various properties (e.g. pointy, stiff, soft) on imported 3D models, which virtually shows the results for previewing and generates G-code files for 3D printing. We demonstrate the design space of X-Hair and evaluate the properties of them with different parameters. Through a series of applications with hair-like structures, we validate X-hair's practical usage of biomimicry, decoration, heat preservation, adhesion, and haptic interaction.2024GWGuanyun Wang et al.Shape-Changing Interfaces & Soft Robotic MaterialsDesktop 3D Printing & Personal FabricationUIST
ProtoDreamer: A Mixed-prototype Tool Combining Physical Model and Generative AI to Support Conceptual DesignPrototyping serves as a critical phase in the industrial conceptual design process, enabling exploration of problem space and identification of solutions. Recent advancements in large-scale generative models have enabled AI to become a co-creator in this process. However, designers often consider generative AI challenging due to the necessity to follow computer-centered interaction rules, diverging from their familiar design materials and languages. Physical prototype is a commonly used design method, offering unique benefits in prototype process, such as intuitive understanding and tangible testing. In this study, we propose ProtoDreamer, a mixed-prototype tool that synergizes generative AI with physical prototype to support conceptual design. ProtoDreamer allows designers to construct preliminary prototypes using physical materials, while AI recognizes these forms and vocal inputs to generate diverse design alternatives. This tool empowers designers to tangibly interact with prototypes, intuitively convey design intentions to AI, and continuously draw inspiration from the generated artifacts. An evaluation study confirms ProtoDreamer’s utility and strengths in time efficiency, creativity support, defects exposure, and detailed thinking facilitation.2024HZHongbo ZHANG et al.Generative AI (Text, Image, Music, Video)Prototyping & User TestingUIST
AutoSpark: Supporting Automobile Appearance Design Ideation with Kansei Engineering and Generative AIRapid creation of novel product appearance designs that align with consumer emotional requirements poses a significant challenge. Text-to-image models, with their excellent image generation capabilities, have demonstrated potential in providing inspiration to designers. However, designers still encounter issues including aligning emotional needs, expressing design intentions, and comprehending generated outcomes in practical applications. To address these challenges, we introduce AutoSpark, an interactive system that integrates Kansei Engineering and generative AI to provide creativity support for designers in creating automobile appearance designs that meet emotional needs. AutoSpark employs a Kansei Engineering engine powered by generative AI and a semantic network to assist designers in emotional need alignment, design intention expression, and prompt crafting. It also facilitates designers' understanding and iteration of generated results through fine-grained image-image similarity comparisons and text-image relevance assessments. The design-thinking map within its interface aids in managing the design process. Our user study indicates that AutoSpark effectively aids designers in producing designs that are more aligned with emotional needs and of higher quality compared to a baseline system, while also enhancing the designers' experience in the human-AI co-creation process.2024LCLiuqing Chen et al.Generative AI (Text, Image, Music, Video)Motor Impairment Assistive Input TechnologiesUIST