Shi (Billy) Chen

I'm a master's student at Carnegie Mellon University's Robotics Institute, in the MRSD program (class of 2028). I received my B.Eng. in Computer Science and Technology from Fudan University in 2026, with an exchange year at UC Berkeley. I'm the Co-founder & CTO of Intuition Core Inc., an AI & Robotics startup developing infrastructure solutions to accelerate real-world robot deployment.

My research interests span robot learning, mobile manipulation, 3D computer vision, and generative modeling. I've been fortunate to work with amazing researchers at UC Berkeley, University of Chicago, University of Cambridge, and Johns Hopkins University. I'm honored to be funded by the National Science Foundation of China under its Youth Fund (one of the highest honors for undergraduates in China; ~120 students nationwide annually).

My mission: I'm driven by the vision of bringing intelligent robots from research labs into the real world, creating transformative solutions that meaningfully improve human lives and unlock new possibilities for society.

shic@intuition.dev  /  shic@andrew.cmu.edu  /  Resume  /  GitHub

News

• [Aug 2026] Released GSSC — our work on generative semantic scene completion is now a preprint on arXiv, with code, checkpoints and the PS³ synthetic dataset all publicly released.
• [Aug 2026] Joined the Robotics Institute at Carnegie Mellon University as an MRSD student, class of 2028.
• [July 2026] Attended the 75th Lindau Nobel Laureate Meeting in Lindau, Germany (28 June – 3 July 2026): a week of inspiring conversations with Nobel Laureates, and wonderful friends made among the ~600 young scientists from around the world.
• [Feb 2026] Honored to be selected as one of only 10 undergraduates from China to attend the 75th Lindau Nobel Laureate Meeting in Germany (June 28 – July 3, 2026), joining ~600 young scientists worldwide to engage with 70+ Nobel Laureates.
• [May 2025] Co-founded Intuition Core Inc. and secured pre-seed funding from Founders Fund.
• [Jan 2025] Started exchange program at UC Berkeley.
• [Sept 2024] Awarded funding by the National Science Foundation of China under its Youth Fund.
• [Aug 2024] Completed summer research at University of Cambridge, graduating with First with Distinction.

Entrepreneurial Experience

Co-founded an AI & Robotics startup developing infrastructure solutions to accelerate real-world robot deployment. In partnership with KUKA, put our intuition-1 model and ISS infrastructure into production on KUKA arms at Midea’s dishwasher factory in Shunde, China, where they run quality inspection on the line 24/7. Secured pre-seed funding from Founders Fund.

Demo video of our Vision-Language-Action (VLA) model trained with our customized data collection pipeline and optimized with our world model pre-training method:

Research

I'm interested in robot learning, mobile manipulation, 3D computer vision, and generative modeling. My research focuses on developing methods that enable machines to perceive, understand, and interact with the physical world. Representative works are highlighted.

Recasts outdoor LiDAR semantic scene completion as a generative problem, using discrete diffusion in three roles: synthesising paired sparse–dense training scenes (PS³), completing a scene from noise, and refining a frozen base model in a single correction step (S²D²). Reaches 38.8% mIoU on the SemanticKITTI hidden test at one step with no test-time augmentation — to our knowledge the best causal, single-sweep, single-sample result on that leaderboard, +2.1 pp over the previous best published score under that restriction; four correction steps with an eight-view D₄ ensemble reach 39.2%, our entry on the public leaderboard. Code, checkpoints and the PS³ synthetic corpus are publicly released. Funded by the National Science Foundation of China Youth Fund.

Extended the Continuous Remeshing pipeline to generate high-quality meshes from single-frame images. Introduced vertex color optimization with novel loss terms. Demonstrated improved mesh quality over baseline Marching Cube algorithm with >70% preference in crowdsourced user study.

Built a custom quadrotor under the Agilicious framework with specialized hardware. Enabled real-time state estimation using SVO Pro algorithm for GPS-free navigation. Fine-tuned Qwen-2.5 3B VLM for onboard deployment on Jetson Orin Nano. Verified feasibility of onboard VLM deployment for real-time quadrotor navigation, reducing hardware costs by several hundred dollars.

Proposed a multimodal diffusion pipeline integrating ControlNet into Stable Diffusion, increasing MediaPipe Confidence scores from 0.248 to 0.556 (2.24x improvement). Created a synthetic dataset of 170,000+ images across 809 gesture types with 83.5% quality rating. Selected for Cambridge Summer Research Programme, graduating with First with Distinction.

Developed a diffusion model to generate 3D bounding boxes and BEV perception data on NuScenes dataset. Combined synthetic input for MagicDrive to create temporally consistent RGB videos. Achieved 2-4% accuracy improvement on downstream tasks including BEV perception and 3D bounding box detection on BEVFusion. Used NeRF-based Nerfacto for controllable 3D scene rendering.

Education

Other Selected Projects

Developed a stateful LLM agent with persistent memory for academic research management. Built Chrome extension to auto-fill graduate school applications. Integrated automated paper discovery using LangChain + GPT-4o. Achieved 98% success rate in automated posting tasks.

Skills & Technical Expertise

Programming Languages: C, C++, Python, OCaml, Lean (Theorem Proving), Verilog HDL, Pascal, MATLAB
Frameworks: PyTorch, PyTorch3d, JAX, OpenCV, NumPy, LangChain
Robotics & Simulation: ROS / ROS2, MuJoCo, OpenAI Gym
Modeling & Design: Blender (3D Modeling), Unity
Tools: Git, Linux, Docker, LaTeX
Languages: English (TOEFL 106, Speaking 25; GRE 336, Quantitative 170)

Thanks to Jon Barron for the template.