Zhixuan Liang
Research Intern at NVIDIA
Hong Kong Island, Hong Kong, China
Summary
🤩
Rockstar🎓
Top SchoolZhixuan Liang is a Ph.D. student in Computer Science at The University of Hong Kong specializing in generative models for planning, robot learning, and embodied AI, with first-author papers in top conferences such as ICML and CVPR. He has seven years of research experience spanning academic and industry labs, including visiting roles at UC Berkeley and internships at NVIDIA and Qwen where he worked on diffusion-based skill and manipulation models like AdaptDiffuser and SkillDiffuser. His work bridges theory and practice—publishing novel methods for robot skill generation and multi-modal planning while demonstrating applicability on dexterous manipulation benchmarks (DexHandDiff). Supervised by leading researchers (Ping Luo, Wenping Wang, Masayoshi Tomizuka), he combines strong foundations from Zhejiang University with cutting-edge lab experience in Hong Kong and the U.S. Actively seeking research intern opportunities starting February or summer 2025, he brings a track record of first-author contributions and cross-institutional collaborations that accelerate embodied AI research. An understated strength is his ability to translate complex diffusion-model ideas into reproducible code and experiments that advance real-world robot capabilities.
7 years of coding experience
The University of Hong Kong (HKU)Bachelor's degree, Automation, Bachelor's degree, Automation at Zhejiang University
Github Skills (39)
pytorch10
diffusion-models10
stable-diffusion10
diffusers10
flax10
text2image10
audio10
deep-learning10
image-generation10
flux10
jax10
reference-implementation7
segmentation7
planning7
computer-vision6
Programming languages (3)
Github contributions (5)
Liang-ZX/OAI-registration
Jul 2020 - Mar 2021
Contributions:94 commits, 89 pushes, 1 branch in 8 months
Liang-ZX/liangzx-cs231n
Aug 2019 - Mar 2021
Stanford cs231n homework
Contributions:15 PRs, 33 pushes, 14 branches in 1 year 7 months
pytorchcs231nstanfordstanford-cs231n
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