Hi, I'm Chan Hee (Luke) Song.

I am a final-year PhD candidate at The Ohio State University advised by Yu Su.

My research focuses on foundation models for embodied intelligence, working on robotics and CUAs.

I have interned at Google Research, NVIDIA Research and Adobe Research.

Find me on , , and .


What's New

October 2025

I’m seeking full-time research opportunities starting in early 2026. Please let me know if my experience aligns with your interests!

October 2025

Watch and Learn, a framework that learns from Internet videos to enhance computer use agents, was featured in VentureBeat!

September 2025

Thrilled to see that RoboSpatial is used by Qwen3-VL and Gemini Robotics! Spatial understanding is the next frontier for MLLMs.

September 2025

Excited to organize Eval&Deploy workshop at CoRL 2025. Also attended by first robotics conference.

August 2025

Honored to serve as an Area Chair for ICLR 2026.

July 2025

Checkout Mind2Web 2, a rigorous benchmark for Deep Research and Agentic Search!

June 2025

Selected to attend CVPR Doctoral Consortium to connect with senior researchers. I'll be mentored by Prof. Katerina Fragkiadaki (CMU).

April 2025

Released Online-Mind2Web benchmark, showing current web agents are far less capable than reported.

March 2025

Interning at Google Cloud AI Research this summer working on multimodal agents. Catch me (again) in Seattle!

Feb 2025

RoboSpatial (Oral) has been accepted to CVPR 2025 with a perfect 5,5,5 score!

Feb 2025

VisualAgentBench has been accepted to ICLR 2025.

Nov 2024

Excited to present RoboSpatial, a work partly done at Nvidia. We present a large-scale 2D/3D spatial understanding dataset and benchmark tailored for robotics. Stay tuned for the full release!

Jun 2024

BioCLIP won the best student paper award at CVPR 2024! Honored to be part of the team.

Feb 2024

BioCLIP, a biology vision foundation model (Oral), and Dual-VCR, a dual-view web-navigation method (Poster) have been accepted to CVPR 2024!

Feb 2024

I will be interning at Nvidia Learning and Perception Research Group this summer. Catch me in Seattle!

Jul 2023

LLM-Planner, a paper on using large language models for vison-and-language navigation accepted to ICCV 2023.

Mar 2023

Our SalsaBot work for Amazon Alexa Prize Challenge has been accepted to the Embodied AI Workshop at CVPR 2023!

Mar 2023

I will be interning at Adobe Research this summer. Catch me in San Jose!


Selected Publications

See full list in Publications.

  • Watch and Learn: Learning to Use Computers from Online Videos

    Chan Hee Song, Yiwen Song, Palash Goyal, Yu Su, Oriana Riva, Hamid Palangi, Tomas Pfister

    preprint Media coverage by VentureBeat Paper

  • RoboSpatial: Teaching Spatial Understanding to 2D and 3D Vision-Language Models for Robotics

    Chan Hee Song, Valts Blukis, Jonathan Tremblay, Stephen Tyree, Yu Su, Stan Birchfield

    CVPR 2025 Oral (0.74%) / Part of GR00T N1.5 / Used by Qwen3-VL & Gemini Robotics Paper Website Code Data

  • BioCLIP: A Vision Foundation Model for the Tree of Life

    Samuel Stevens, Jiaman Wu, Matthew J Thompson, Elizabeth G Campolongo, Chan Hee Song, David Edward Carlyn, Li Dong, Wasila M Dahdul, Charles Stewart, Tanya Berger-Wolf, Wei-Lun Chao, Yu Su

    CVPR 2024 Best Student Paper Award (0.03%) Paper Website Code Data

  • LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models

    Chan Hee Song, Jiaman Wu, Clayton Washington, Brian M. Sadler, Wei-Lun Chao, Yu Su

    ICCV 2023 Top 5 Most Cited AI Paper on arXiv (2022) Paper Website Code

Contact
Email: 1ch[LAST_NAME]@gmail.com

Feel free to contact me on anything including collaboration, job opportunities, or just a friendly hello :)