Building a Robot Learning Pipeline with SO-101
Hardware bring-up, teleoperation, and data collection
Read articleAbout Me
Hi, I'm Xi Fang. I completed my PhD in the Department of Biomedical Engineering at Rensselaer Polytechnic Institute, where I was advised by Pingkun Yan, and received my bachelor's degree from the School of Computer Science at Wuhan University, where I worked with Bo Du.
I am currently a machine learning engineer at Noah Medical. My earlier experience includes AI and computer vision research internships at Infervision, Tsinghua University's State Key Laboratory of Intelligent Technology and Systems, and the Immersive Media Lab of Tencent America.
Technical & Research Focus
I build computer vision and multimodal ML systems for robotics, medical imaging, and deployable real-world applications, with a focus on turning strong research into deployable systems, supported by publications, technical reports, and projects.
- Computer Vision: multi-view geometry, 3D reconstruction, NeRF, Gaussian splatting, implicit neural representations, and perception tasks such as segmentation, detection, and registration.
- Robotics Learning: multimodal learning, motion transfer, VLMs, VLAs, world models, and deployable systems for robotics and embodied intelligence.
- Medical Image Analysis: clinically grounded methods for medical imaging, surgical planning, image analysis, in-context learning, and reliable decision support systems.
Selected Blogs
Recent News
Aug 2026. As part of a Fuyao Program event, I volunteered to present the evolution of AI and robotics at the Computer History Museum. More details.
Jun 2024. Received the Runner-Up prize for the NVIDIA Bench-to-Bedside Award at IPCAI 2024.
Sep 2022. Received the Young Scientist Award at MICCAI 2022.
Jun 2022. Received the Student Travel Award at MICCAI 2022.
Nov 2020. COVID-19 patient outcome prediction work was reported by News10 and RPI Campus News.