Open 3D World Models-Lingjing

EngineeringAI Lab

We build 3D world models that connect representation, spatial synthesis, interaction dynamics, and decision intelligence for agents in digital worlds.

EngineeringAI Lab logo mark

Who We Are

A compact team for 3D world model research

EngineeringAI Lab was established by AP Huadong Mo at UNSW and Prof. Daoyi Dong at UTS, together with Zhenhong Sun. Zhenhong leads the practical research directions and coordinates the shared 3D World Model agenda.

EngineeringAI Lab is an innovation team focused on 3D World Model research and engineering deployment. We believe truly intelligent systems must understand, model, and interact with the 3D physical world, so we build world models with spatial perception, scene understanding, dynamic simulation, and interaction capabilities, connecting foundational construction, perceptual understanding, and decision-making action.

Open to strong candidates

Interested in working with us?

We are recruiting PhD students or Research Assistants at UNSW and UTS. We welcome candidates with curiosity, passion, and engagement. Send a short introduction, and CV to Huadong Mo and Daoyi Dong. For informal questions, contact Zhenhong Sun.

Contact Us

We Work On

Four shared directions for open 3D world models

Our research agenda follows the same four directions as LingJing 3D World Model work, turning a research vision into coordinated lab systems.

01

Foundation Representation and Manipulation

Compact and controllable 3D asset representations for reconstruction, editing, decomposition, and state prediction.

  • Unified 3D asset representations
  • Single-view and multi-view reconstruction
  • Part-aware structure decomposition
02

Spatial Understanding and Synthesis

Agentic generation pipelines and engine-grounded tools for coherent 3D scenes, simulation data, and spatial evaluation.

  • Compositional 3D scene generation
  • Engine-grounded spatial perception
  • Simulation data and benchmarks
03

Interaction Dynamics and Motion

Expressive avatars, human-scene interaction, and multi-person motion generation for dynamic digital worlds.

  • 2D and 3D talking avatars
  • Human-scene interaction modeling
  • Multi-agent motion and social dynamics
04

Decision Intelligence and Reasoning

LLM-based reasoning, language-guided planning, reinforcement learning, and decision systems for agents in 3D worlds.

  • LLM-based world reasoning
  • Language-guided planning
  • Decision making in 3D environments

Highlights

Milestone

StoryBlender accepted to ECCV

StoryBlender is the first team-led paper from EngineeringAI Lab accepted to ECCV, marking an important milestone for our 3D World Model program.

Culture

Research quality, engineering execution

We value people who can turn ideas into datasets, simulators, tools, benchmarks, demos, and reproducible research infrastructure.

News

Recent lab updates

  1. StoryBlender accepted to ECCV

    StoryBlender became the first EngineeringAI Lab team-led paper accepted to ECCV.

  2. Zhenhong invited as Area Chair for NeurIPS 2026

    The invitation reflects the lab's growing engagement with top-tier machine learning research communities.

Latest Posts

Notes from the lab

Short research notes and project updates from our 3D World Model agenda.

StoryBlender becomes our first ECCV team paper

A first team-level acceptance shows how the lab can coordinate research, engineering, writing, and system building around open 3D world models.

Why talking avatars need spatial dynamics

3DXTalker connects identity, lip motion, emotion, and head movement to make expressive 3D digital humans more controllable.

What we look for in new lab members

We look for people who can think from first principles, implement carefully, communicate clearly, and stay curious across disciplines.