QuantEcon/lecture-python.myst
Jul 2025 – Jul 2025
1 Month active
Languages Used
JAXPython
Technical Skills
JAXModel ImplementationNumerical ComputationScientific Computing
John Stachurski
PROFILE
John Stachurski
John Stachurski developed a JAX-based backend for the McCall model in the QuantEcon/lecture-python.myst repository, focusing on improving simulation speed and numerical stability. He migrated the model’s computations from Numba to JAX, leveraging just-in-time compilation and vectorized array operations to enhance performance. By introducing a Model NamedTuple, he encapsulated parameters and state, streamlining downstream usage and future extensions. John refactored core functions to utilize JAX’s array operations, resulting in a more maintainable and reliable codebase. His work demonstrates depth in scientific computing and model implementation, providing a robust foundation for teaching materials and downstream analytical applications.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
234
Activity Months1
Your Network
9 people
Work History
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025: Delivered a JAX-based McCall model backend for QuantEcon/lecture-python.myst, refactoring the model to use a Model NamedTuple for parameter encapsulation and updating solve_model and update to leverage JAX jit and vectorized array operations. This work migrates from Numba to JAX, enabling faster simulations, improved numerical stability, and a more reliable interface for downstream analyses and teaching materials.
1 Commits • 1 Features
Jul 1, 2025July 2025: Delivered a JAX-based McCall model backend for QuantEcon/lecture-python.myst, refactoring the model to use a Model NamedTuple for parameter encapsulation and updating solve_model and update to leverage JAX jit and vectorized array operations. This work migrates from Numba to JAX, enabling faster simulations, improved numerical stability, and a more reliable interface for downstream analyses and teaching materials.
July 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JAXPython
Technical Skills
JAXModel ImplementationNumerical ComputationScientific Computing
Repositories Contributed To
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