nvidia-cosmos/cosmos-rl
Dec 2025 – Mar 2026
4 Months active
Languages Used
PythonRSTTOMLbashpython
Technical Skills
Data ProcessingMachine LearningPythonPython programmingReinforcement Learningdeep learning
LiangHao
PROFILE
Lianghao
Worked on the nvidia-cosmos/cosmos-rl repository to deliver advanced reinforcement learning features and robust environment integrations over four months. Developed and enhanced Variable Length Attention workflows, unified rollout logic across simulators, and integrated new environments such as Robotwin and ManiSkill3. Leveraged Python and deep learning frameworks to implement asynchronous programming, distributed simulation, and CI/CD automation, improving both experimentation speed and reliability. Focused on reproducible training pipelines, scalable environment wrappers, and comprehensive documentation to support onboarding and adoption. The work emphasized robust validation, automated testing, and streamlined configuration, enabling faster, safer policy experimentation and efficient model-based robotics development across diverse simulation platforms.
Overall Statistics
Feature vs Bugs
88%Features
Repository Contributions
13Total
Bugs
1
Commits
13
Features
7
Lines of code
20,972
Activity Months4
Your Network
1647 peopleSame Organization
@nvidia.com1624
Work History
March 2026
3 Commits • 3 Features
Mar 1, 2026March 2026 summary: Delivered three core features in nvidia-cosmos/cosmos-rl that expand RL experimentation, improve CI/testing, and broaden environment coverage. Cosmos Policy model support integrated with the VLA framework, including configuration, build/test workflow, and architecture updates to accommodate the new policy type (commit d2d4ff671ccb8a6214c48e744cf13599294be133). RoboTwin environment setup and CI integration added scripts to install dependencies and configure RoboTwin and Libero environments, enabling automated CI testing (commit 188e9b10bd16b3f7a7b8f71deac7c891aa884f40). ManiSkill3 environment support introduced an environment wrapper and testing suite to validate functionality and performance (commit 444a84a2f0a6bac415f37d43fc7a3acd6f08f0b1). No major bugs fixed are documented this month; the focus was on feature delivery and CI/automation. Overall impact: enhanced cross-environment experimentation, reduced integration cycles, and stronger testing coverage, delivering business value by accelerating safe policy experimentation and improving reliability. Technologies/skills demonstrated: RL policy integration, VLA framework adaptation, environment wrappers, CI/CD automation, scripting for environment provisioning and testing.
3 Commits • 3 Features
Mar 1, 2026March 2026 summary: Delivered three core features in nvidia-cosmos/cosmos-rl that expand RL experimentation, improve CI/testing, and broaden environment coverage. Cosmos Policy model support integrated with the VLA framework, including configuration, build/test workflow, and architecture updates to accommodate the new policy type (commit d2d4ff671ccb8a6214c48e744cf13599294be133). RoboTwin environment setup and CI integration added scripts to install dependencies and configure RoboTwin and Libero environments, enabling automated CI testing (commit 188e9b10bd16b3f7a7b8f71deac7c891aa884f40). ManiSkill3 environment support introduced an environment wrapper and testing suite to validate functionality and performance (commit 444a84a2f0a6bac415f37d43fc7a3acd6f08f0b1). No major bugs fixed are documented this month; the focus was on feature delivery and CI/automation. Overall impact: enhanced cross-environment experimentation, reduced integration cycles, and stronger testing coverage, delivering business value by accelerating safe policy experimentation and improving reliability. Technologies/skills demonstrated: RL policy integration, VLA framework adaptation, environment wrappers, CI/CD automation, scripting for environment provisioning and testing.
March 2026
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary: Delivered Robotwin environment support in the VLA framework for cosmos-rl, including configuration files, environment wrappers, and dataset handling to enable improved training and evaluation of robotic tasks. This integration provides a robust, reproducible setup for robotic experiments and aligns cosmos-rl with Robotwin workflows. No major bugs fixed this month. Impact: faster experimentation cycles, clearer traceability, and a scalable path for future environment integrations. Technologies demonstrated: Python, VLA framework integration, environment wrappers, dataset pipelines, and config-driven development.
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary: Delivered Robotwin environment support in the VLA framework for cosmos-rl, including configuration files, environment wrappers, and dataset handling to enable improved training and evaluation of robotic tasks. This integration provides a robust, reproducible setup for robotic experiments and aligns cosmos-rl with Robotwin workflows. No major bugs fixed this month. Impact: faster experimentation cycles, clearer traceability, and a scalable path for future environment integrations. Technologies demonstrated: Python, VLA framework integration, environment wrappers, dataset pipelines, and config-driven development.
January 2026
4 Commits • 2 Features
Jan 1, 2026Delivered cross-environment PI05 model support and simulation enhancements for Cosmos-RL, enabling continuous Libero simulation with asynchronous resets and substantial speedups. Implemented unified rollout logic across OpenPI and Libero simulators and extended PI05 support to B1K with improved training configuration and data handling. Published Cosmos-RL Vision-Language-Action (VLA) model support documentation to accelerate adoption and onboarding. No major bugs were reported this month; the work focused on feature delivery, reliability, and documentation. Business value includes faster experimentation and reproducibility across simulators, enabling more efficient RL development and faster time-to-value for model-based workloads. Technologies demonstrated include distributed simulation, asynchronous reset mechanics, performance optimizations, cross-repo coordination, and thorough documentation.
4 Commits • 2 Features
Jan 1, 2026Delivered cross-environment PI05 model support and simulation enhancements for Cosmos-RL, enabling continuous Libero simulation with asynchronous resets and substantial speedups. Implemented unified rollout logic across OpenPI and Libero simulators and extended PI05 support to B1K with improved training configuration and data handling. Published Cosmos-RL Vision-Language-Action (VLA) model support documentation to accelerate adoption and onboarding. No major bugs were reported this month; the work focused on feature delivery, reliability, and documentation. Business value includes faster experimentation and reproducibility across simulators, enabling more efficient RL development and faster time-to-value for model-based workloads. Technologies demonstrated include distributed simulation, asynchronous reset mechanics, performance optimizations, cross-repo coordination, and thorough documentation.
January 2026
December 2025
5 Commits • 1 Features
Dec 1, 2025Month: 2025-12. This period focused on stabilizing and scaling Variable Length Attention (VLA) workflows in the nvidia-cosmos/cosmos-rl repository, while tightening rollout validation. Delivered end-to-end VLA enhancements, improved simulation capabilities, and hardened validation to support faster, more reliable experimentation with business value in mind.
December 2025
5 Commits • 1 Features
Dec 1, 2025Month: 2025-12. This period focused on stabilizing and scaling Variable Length Attention (VLA) workflows in the nvidia-cosmos/cosmos-rl repository, while tightening rollout validation. Delivered end-to-end VLA enhancements, improved simulation capabilities, and hardened validation to support faster, more reliable experimentation with business value in mind.
Activity
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Quality Metrics
Correctness83.0%
Maintainability81.6%
Architecture83.0%
Performance83.0%
AI Usage46.2%
Skills & Technologies
Programming Languages
PythonRSTTOMLbashpython
Technical Skills
AI model trainingAsynchronous ProgrammingCI/CDData ProcessingDeep LearningDevOpsEnvironment SimulationMachine LearningModel TrainingPythonPython DevelopmentPython programmingReinforcement LearningRoboticsScripting
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