Dizhi Ma

schoolPurdue Universitybar_chart#2448 Global Rank

Total Papers

HCI Rank

#2448

Research Areas

Years Active

Recent Publications

JustShape: Exploring Co-Speech Gestures for Multimodal LLM-Powered 3D Parametric Modeling

Parametric modeling is a prevailing 3D modeling approach in design, architecture, and engineering. The emergence of multimodal large language models (LLMs) brings a new opportunity to lower the entry barriers to this powerful tool. However, describing 3D geometries through natural language can be fuzzy and challengi…

CHI '264th AuthorAR Navigation & Context Awareness +2

ARify: Leveraging Narrated Instructional Videos to Create Augmented Reality Tutorials for Procedural Tasks

Augmented Reality (AR) tutorials enhance procedural task learning by providing situated, step-by-step guidance. Yet, creating such tutorials requires AR authoring expertise, posing a significant entry barrier. To lower this barrier, we introduce ARify, an authoring system that semi-automatically transforms narrated in…

CHI '261st AuthorHuman Pose & Activity Recognition +2

AgentCoach: LLM-Based Adaptive Coaching Feedback for Motor Skill Learning

We present AgentCoach, an LLM-powered system that provides adaptive feedback for motor skill learning from tutorial videos. The system works by extracting key coaching points (CPs) and compiling CP-specific evaluators that map each cue to measurable kinematic parameters. This process allows AgentCoach to connect high-…

DIS '252nd AuthorHand Gesture Recognition +2

GesPrompt: Leveraging Co-Speech Gestures to Augment LLM-Based Interaction in Virtual Reality

Large Language Model (LLM)-based copilots have shown great potential in Extended Reality (XR) applications. However, the user faces challenges when describing the 3D environments to the copilots due to the complexity of conveying spatial-temporal information through text or speech alone. To address this, we introduce…

UIST '241st AuthorFull-Body Interaction & Embodied Input +2

avaTTAR: Table Tennis Stroke Training with On-body and Detached Visualization in Augmented Reality

Table tennis stroke training is a critical aspect of player development. We designed a new augmented reality (AR) system, avaTTAR, for table tennis stroke training. The system provides both “on-body” (first-person view) and “detached” (third-person view) visual cues, enabling users to visualize target strokes and cor…

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