Multimodal Intelligence Lab (MILab)

The Multimodal Intelligence Lab (MILab) is a University of Washington research group based at UW Tacoma. We develop multimodal AI systems that connect perception, language, memory, reasoning, and action. Our work spans foundation models, embodied agents, robotics, mobility intelligence, public safety, and human-centered decision support.

What We Study Research directions Meet the Team People at MILab
Multimodal Robotics

From perception to action

We connect visual evidence, language, and control for reliable manipulation and embodied decision-making in physical workspaces.

Embodied AI

Agents that understand people and places

We study how agents use memory, goals, and prediction to navigate and interact in human environments over longer horizons.

HA-VLN 2.0 benchmark and leaderboard figure
Human-Aware Intelligence

Reasoning with people, space, and goals

We model social context and spatial evidence so AI agents can act safely around people in shared spaces.

Language-conditioned world modeling for visual navigation figure
World Models

Learning environments from multimodal evidence

We build predictive models that connect instructions, observations, and possible future states for embodied planning.

Unified world model navigation results figure
Planning and Foresight

Predictive models for embodied decisions

We use memory and simulation to help agents compare possible futures before acting in dynamic scenes.

Agentic world modeling four regimes figure
Trustworthy AI Systems

From models to safe deployment

We design AI systems for mobility, public safety, and secure decision support under operational constraints and risks.

Research Directions

Multimodal models, embodied agents, and deployable systems for public-interest AI.

MILab connects model foundations, embodied reasoning, and deployable systems for mobility, public safety, and human-centered decision support.

Direction 01

Foundation Models

Multimodal models for perception, reasoning, learning, and generation across language, vision, video, audio, and structured signals.

Direction 02

Embodied Agents

Embodied agents for navigation, interaction, planning, memory, and control in human-aware physical and simulated environments.

Direction 03

Deployable Systems

Deployable systems for mobility, safety, sensing, monitoring, and decision-making with secure and responsible operation.

Lab Updates

Recent news and selected publications

News Publications

Recent News

  1. 2026 GSFEI Top Scholar Award

    Fengyi Wu received GSFEI recognition for research excellence.

  2. ACL 2026 paper acceptances

    Sign-language survey and GoVIG navigation papers accepted to ACL 2026.

  3. ICLR 2026 oral presentation

    Lossless hierarchical decoding work accepted as an ICLR 2026 oral paper.

  4. NeurIPS 2025 oral presentation

    MaxSup, with former visiting student Yuxuan Zhou, was accepted as a NeurIPS 2025 oral paper.

  5. Carwein-Andrews Ph.D. Fellowship

    Yifei Dong recognized for world-model navigation research.

  6. CVPR Anti-UAV Best Paper

    Securing the Skies received Best Paper workshop recognition.

Recent Publications

  1. HA-VLN 2.0 benchmark overview
  2. Language-conditioned world modeling overview
  3. Human-aware vision-and-language navigation overview
  4. Emotion-LLaMA overview
  5. Lossless hierarchical speculative decoding overview
  6. MaxSup visualization
Prospective Students and Collaborators

Join MILab research at UW.

MILab welcomes prospective Ph.D. students, postdoctoral researchers, UW students across Seattle, Tacoma, and Bothell, and collaborators interested in multimodal AI, embodied intelligence, and deployable systems.

Review Pathways Join MILab