
Brian Shu
M.S. Computer Science, Purdue · CoRAL Lab
I’m Brian Shu, an M.S. student in Computer Science at Purdue University, working in the Cognitive Robot Autonomy & Learning (CoRAL) Lab with Prof. Ahmed H. Qureshi. I work on robot learning for long-horizon manipulation: imitation learning, post-training vision-language-action (VLA) models, and the benchmarks that tell you whether a policy actually works.
Right now that is a dishwasher-loading policy in NVIDIA Isaac Lab. Before Purdue I built the subtask environments and asset pipeline for Fiatlux, a humanoid ladder-climbing benchmark under review at ICRA 2027, and a force-monitored expert for cable insertion on a UR5.
I’m looking for a robotics research internship for Summer 2027 and can work full-time from May 10 to August 20, 2027. If your lab or team works on manipulation, imitation learning or evaluation, I would like to hear from you.
Projects
Four projects, each with its own page: what I built, media from the simulator, and the code.

Fiatlux
A long-horizon benchmark in which a simulated Unitree G1 humanoid climbs a ladder and replaces a light bulb, built in NVIDIA Isaac Lab.

Dishwasher loading
A general dishwasher-loading manipulation policy in NVIDIA Isaac Lab, built on simulated dish assets I released publicly.
Cable insertion
A force-monitored expert policy and an imitation-learning pipeline for cable insertion on a UR5, built for the AI for Industry Challenge.
DCVLR
Data Curation for Visual-Language Reasoning, a pipeline that generates synthetic multimodal question-answer pairs with reasoning steps and uses them to fine-tune Qwen2.5-VL.
Publications

Fiatlux: A Long-Horizon Benchmark for Humanoid Ladder Climbing and Light-Bulb Replacement
A 12-subtask benchmark in NVIDIA Isaac Lab in which a simulated Unitree G1 humanoid moves a ladder, climbs it and replaces a ceiling light bulb.
Experience
- CoRAL Lab, Purdue — Graduate Researcher
Building a general dishwasher-loading manipulation policy in NVIDIA Isaac Lab; released the simulated dish assets.
- HawAII, UH Mānoa — Research Assistant
Built the 12 subtask environments and asset pipeline for the Fiatlux benchmark, and the force-monitored expert and imitation-learning pipeline for the AI for Industry Challenge.
- Hyundai Card — Data Science Intern
RAG pipeline for text-to-SQL with self-consistency decoding; migrated to an open-source model while keeping 80% execution accuracy.
- UH Mānoa — Software Verification Developer
Isabelle/HOL proofs of functional correctness, following the seL4 and RT-11 verification efforts.
- UH Mānoa — Research Assistant
Efficient simulation of a biological reaction model, with 2D and 3D visualization of the results.
More work
- Jane Street Real-Time Market Data Forecasting
Supervised autoencoder + MLP; ranked 440 of 3,000 (top 15%).
- Spinner Dolphin Photo Grading Protocol
Multi-stage model that detects, rates and classifies spinner dolphins by fin distinctiveness.
- BirdCLEF 2024
Transfer-learned MobileNet-v2 on spectrograms to identify under-studied Indian bird species.
- Higgs Boson Detection
Compared scikit-learn classifiers; 11th of 52 on the public leaderboard.
- OpenAI CarRacing
2D CNN driving agent in TensorFlow for randomly generated tracks.
- Full Cycle TakeOut
MERN and Meteor web app for ZeroWaste Oʻahu.
- Protein folding
Hydrophobic-polar lattice model solved by recursive backtracking.
- PANDA programming club
Designed an algorithms curriculum and led small-group sessions; 2023 Best Officer award.
- ACM at Mānoa
Maintained the chapter website and built internal tools for the leadership team.
Contact
Email is the quickest way to reach me: [email protected]. I'm also on GitHub, Hugging Face and LinkedIn.