Chengyang Zhao
Scholar

Chengyang Zhao

Google Scholar ID: XIFrv2cAAAAJ
Carnegie Mellon University
RoboticsMachine Learning3D Computer Vision
Citations & Impact
All-time
Citations
190
 
H-index
5
 
i10-index
4
 
Publications
7
 
Co-authors
0
 
Resume (English only)
Academic Achievements
  • - Publications:
  • - DYMO-Hair: Generalizable Volumetric Dynamics Modeling for Robot Hair Manipulation (Arxiv, 2025)
  • - Dita: Scaling Diffusion Transformer for Generalist Vision-Language-Action Policy (ICCV, 2025)
  • - RoboVerse: Towards a Unified Platform, Dataset and Benchmark for Scalable and Generalizable Robot Learning (RSS, 2025)
  • - GAPartManip: A Large-scale Part-centric Dataset for Material-Agnostic Articulated Object Manipulation (ICRA, 2025)
  • - D3RoMa: Disparity Diffusion-based Depth Sensing for Material-Agnostic Robotic Manipulation (CoRL, 2024)
  • - TextPSG: Panoptic Scene Graph Generation from Textual Descriptions (ICCV, 2023)
  • - GAPartNet: Cross-Category Domain-Generalizable Object Perception and Manipulation via Generalizable and Actionable Parts (conference not specified)
Research Experience
  • - Projects: DYMO-Hair, Dita, RoboVerse, GAPartManip, D3RoMa, TextPSG, GAPartNet, etc.
  • - Position: Master's student
Education
  • - Degree: Master's
  • - University: Carnegie Mellon University
  • - Advisor: Prof. Jean Oh
  • - Duration: 2023 to present
  • - Major: Robotics
  • - Degree: Bachelor's
  • - University: Yuanpei College, Peking University
  • - Advisors: Prof. He Wang, Prof. Chuang Gan
  • - Duration: Undergraduate years
  • - Major: Data Science (Computer Science + Statistics)
Background
  • - Research Interests: Intersection of robotics and machine learning, with a focus on robot manipulation
  • - Field: Data Science (Computer Science + Statistics)
  • - Introduction: Currently a second-year master's student at Carnegie Mellon University's Robotics Institute, focusing on developing structured models for effective and generalizable robot manipulation.
Miscellany
  • - Seeking PhD positions starting in Fall 2026
  • - Open to collaboration opportunities
  • - Contact information includes email, Google Scholar, LinkedIn, Github, X (Twitter)
Co-authors
0 total
Co-authors: 0 (list not available)