Robotics · Georgia Tech

Rui Yan

Building robots for
the real world.

I work on practical, deployable robotic systems that bridge research and real-world industrial applications.

Rui Yan
Ph.D. student in RoboticsGeorgia Institute of Technology

A little background

I am a first-year Ph.D. student in Robotics at Georgia Tech, advised by Prof. Ye Zhao. I received my M.S. in Electrical and Computer Engineering from UC San Diego, advised by Prof. Xiaolong Wang. I previously worked with Prof. Fei Liu and Prof. Tianshu Yu. I am interested in building practical and deployable robotic systems that bridge research and real-world industrial applications.

Latest news

Learning. Manipulation. Interaction.

Publications.

Google Scholar

Latest publicationConference on Robot Learning (CoRL 2026)

FACT: Failure-Aware Causal Training for World-Action Models

Quanquan Peng*, Yutong Liang*, Rui Yan, Nicklas Hansen, Xiaolong Wang

Conference on Robot Learning (CoRL 2026)

Long-Horizon Manipulation via Trace-Conditioned VLA Planning

Isabella Liu, An-Chieh Cheng, Rui Yan, Geng Chen, Ri-Zhao Qiu, Xueyan Zou, Sha Yi, Hongxu Yin, Xiaolong Wang, Sifei Liu

arXiv preprint

Human-Robot Copilot for Data-Efficient Imitation Learning

Rui Yan, Zaitian Gongye, Lars Paulsen, Xuxin Cheng, Xiaolong Wang

Robotics: Science and Systems (RSS 2025) Workshop

ACE-F: A Cross Embodiment Foldable System with Force Feedback for Dexterous Teleoperation

Rui Yan, Jiajian Fu, Shiqi Yang, Lars Paulsen, Xuxin Cheng, Xiaolong Wang

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2026)

EgoVLA: Learning Vision-Language-Action Models from Egocentric Human Videos

Ruihan Yang, Qinxi Yu, Yecheng Wu, Rui Yan, Borui Li, An-Chieh Cheng, Xueyan Zou, Yunhao Fang, Hongxu Yin, Sifei Liu, Song Han, Yao Lu, Xiaolong Wang

From ideas to systems

Selected projects.

Attention-Driven Depth Fusion: Leveraging Focus and Single-Image Priors with Self-Cross Attention — method overview

Attention-Driven Depth Fusion: Leveraging Focus and Single-Image Priors with Self-Cross Attention

Rui Yan, Zaitian Gongye

We propose an end-to-end model that fuses a single RGB image and its defocus map using attention mechanisms to estimate depth. Instead of handcrafted fusion, it uses self- and cross-attention for uncertainty-aware refinement.

Education & experience.

Education

  1. Aug 2026 — present

    Georgia Tech

    Ph.D. in Robotics

    Advisor: Prof. Ye Zhao.
  2. Sep 2024 — Jun 2026

    UC San Diego

    M.S. in Electrical and Computer Engineering

    Machine Learning and Data Science

    Advisor: Prof. Xiaolong Wang.
  3. Sep 2020 — Jun 2024

    Chongqing University

    B.Eng. in Artificial Intelligence

    X-innovation Class

    Advisors & colleges
    • 2020–2022 Hongshen Honors School
    • 2022–2024 National Elite Institute of Engineering

Research & industry

  1. Jun 2023 — Dec 2023

    Research Assistant

    The Chinese University of Hong Kong, Shenzhen

    Advisor: Prof. Tianshu Yu.
  2. Jul 2021 — Aug 2021

    Robotics Engineering Intern

    Ningbo TechX Institute

Rui Yan · Georgia Tech

Let’s connect.