newton-physics/newton
Aug 2025 – Aug 2025
1 Month active
Languages Used
C++Python
Technical Skills
C++Differentiable SimulationGradient-Based OptimizationPhysics SimulationPythonSoftware Engineering
mzamoramora-nvidia
PROFILE
Mzamoramora-nvidia
In August 2025, Miguel Zamora Mora enhanced the newton-physics/newton repository by developing two core features focused on physics simulation and differentiable optimization. He introduced a configurable triangle-contact toggle within the cloth simulation module, enabling users to control triangle contact force calculations and validating the feature with targeted unit tests. Additionally, Miguel built a differentiable simulation suite with five reference examples, comprehensive documentation, and robust test coverage, supporting gradient-based parameter optimization workflows. His work, implemented in C++ and Python and leveraging GPU computing with Warp, deepened the library’s simulation fidelity and expanded its utility for downstream research and engineering projects.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
2,138
Activity Months1
Your Network
1370 people
Work History
August 2025
2 Commits • 2 Features
Aug 1, 2025In August 2025, contributed to the Newton physics library with tangible improvements in physics fidelity and differentiable simulation capabilities, validated by tests and aligned with downstream usage. Major features introduced include a configurable triangle-contact toggle in cloth simulation and a new differentiable simulation (diffsim) suite with multiple reference examples, documentation, and tests. These changes create new avenues for optimization, design iteration, and robust simulation in downstream projects.
2 Commits • 2 Features
Aug 1, 2025In August 2025, contributed to the Newton physics library with tangible improvements in physics fidelity and differentiable simulation capabilities, validated by tests and aligned with downstream usage. Major features introduced include a configurable triangle-contact toggle in cloth simulation and a new differentiable simulation (diffsim) suite with multiple reference examples, documentation, and tests. These changes create new avenues for optimization, design iteration, and robust simulation in downstream projects.
August 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
C++Differentiable SimulationGradient-Based OptimizationPhysics SimulationPythonSoftware EngineeringTestingWarp (GPU Computing)
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