Research

I work on vision-language-action models, embodied reasoning, and robot learning — with a focus on systems that are validated on real hardware, not just in simulation. * denotes equal contribution.

Vision-Language-Action ModelsRobot LearningActive PerceptionEmbodied ReasoningReal-World EvaluationSim-to-Real Transfer

Featured

Under Review2026

TiPToP: A Modular Planning-Based Robot Manipulation System

William Shen, Nishanth Kumar, Sahit Chintalapudi, Jie Wang, Christopher Watson, Edward S. Hu, Jing Cao, Dinesh Jayaraman, Leslie Pack Kaelbling, Tomás Lozano-Pérez

We propose a planning-based robotics system that solves complex real-world manipulation tasks directly from raw pixels and natural-language commands. Validated 'in-the-wild' at GRASP Lab.

Paper Code

TAMPVLAsEvaluation

NeurIPS 2025 & ARLET Workshop2026

AAWR: Real World Reinforcement Learning of Active Perception Behaviors

Edward S. Hu*, Jie Wang*, Xingfang Yuan*, Fiona Luo, Muyao Li, Gaspard Lambrechts, Oleh Rybkin, Dinesh Jayaraman

We propose a simple robot learning recipe leveraging privileged information to train active perception policies on real robots.

Paper Code

RLActive PerceptionVLAs

2026· 1 paper

Under Review2026

OmniGuide: Universal Guidance Fields for Enhancing Generalist Robot Policies

Yunzhou Song*, Long Le*, Yong-Hyun Park, Jie Wang, Junyao Shi, Lingjie Liu, Jiatao Gu, Eric Eaton, Dinesh Jayaraman, Kostas Daniilidis

A flexible framework that improves VLA performance on spatial reasoning tasks by leveraging prior knowledge from 3D foundation models, semantic-reasoning VLMs, and human trajectory demonstrations.

Paper

Guidance3DVLAsSpatial Reasoning

2025· 3 papers

CoRL2025🏆 Oral Presentation

RoboArena: Distributed Real-World Evaluation of Generalist Robot Policies

RoboArena Team

A distributed real-world evaluation framework for generalist robot policies.

Paper Code

VLAsReal-World Evaluation

ICRA2025

ZeroMimic: Distilling Robotic Manipulation Skills from Web Videos

Junyao Shi, Zhuolun Zhao, Tianyou Wang, Ian Pedroza, Amy Luo, Jie Wang, Jason Ma, Dinesh Jayaraman

Learning robotic manipulation skills from web videos with zero-shot generalization.

Paper Code

Learning from VideosArticulationImitation Learning

IEEE Transactions on Intelligent Transportation Systems2025

Visionary Co-Driver: LLMs Enhance Driver Risk Perception with ARHUD

Xiang Wei, Ziyue Lei, Jie Wang, Qi Zheng, Yingying Huang, Tianyi Zhang, Lingyun Sun

Using LLMs and Vision foundation models to analyze autonomous driving road scene, modeling the behavior of pedestrians. Construct a HUD system to evaluate the driver interaction.

Paper Code

Autonomous DrivingLLMsHuman-Computer Interaction