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Mohammad Linjawi

PROFILE

Mohammad Linjawi

Over a three-month period, this developer enhanced data processing and evaluation workflows across multiple repositories, including pytorch/torchtune, mathworks/arrow, and facebookincubator/velox. They delivered a configurable GEMMA evaluation pipeline in torchtune using PyTorch and YAML, enabling reproducible model assessments. In mathworks/arrow, they migrated tutorials to the latest Arrow C++ API, resolving build failures and improving onboarding reliability. Their work in velox and related Spark integrations focused on ANSI-mode casting semantics, concurrency safety, and expanded test coverage, leveraging C++, Java, and SQL. These contributions improved data correctness, code maintainability, and operational stability for machine learning and analytics pipelines.

Overall Statistics

Feature vs Bugs

40%Features

Repository Contributions

6Total
Bugs
3
Commits
6
Features
2
Lines of code
840
Activity Months3

Work History

February 2026

4 Commits • 1 Features

Feb 1, 2026

February 2026 monthly summary focused on delivering ANSI-mode casting semantics in Spark integration, improving concurrency safety, and expanding test coverage across Velox and Gluten. Key outcomes include robust data correctness in ANSI mode, safer concurrent data structures, and stronger alignment with Spark behavior and documentation, reducing operational risk for Spark-based data pipelines.

November 2024

1 Commits

Nov 1, 2024

2024-11: MathWorks Arrow repository — Updated example tutorials to migrate to parquet::arrow::OpenFile API in line with the latest Arrow C++ version, resolving build failures and improving tutorial reliability for developers and downstream users. Emphasizes business value by ensuring tutorials reflect current APIs, reducing maintenance risk and improving onboarding.

October 2024

1 Commits • 1 Features

Oct 1, 2024

In 2024-10, delivered GEMMA Evaluation Configuration and Registry Integration for pytorch/torchtune, introducing a dedicated configuration file and registering it in the recipe registry to enable parameterized GEMMA model evaluation. This enables reproducible, configurable evaluation workflows, improves model assessment, and enhances discoverability of evaluation pipelines. No major bugs fixed this month; the focus was on feature delivery and pipeline robustness. Key technical outcomes include a configurable GEMMA evaluation, recipe-registry integration, and full commit traceability (c70ad2986177d28521a87abf28322037b2476866, '1810 move gemma evaluation (#1819)').

Activity

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Quality Metrics

Correctness100.0%
Maintainability86.6%
Architecture90.0%
Performance86.6%
AI Usage20.0%

Skills & Technologies

Programming Languages

C++JavaMarkdownPythonYAML

Technical Skills

API DevelopmentC++C++ developmentJavaPyTorchSQLSoftware MaintenanceTestingconcurrent programmingconfiguration managementdata processingdocumentationmachine learningmodel evaluationunit testing

Repositories Contributed To

5 repos

Overview of all repositories you've contributed to across your timeline

facebookincubator/velox

Feb 2026 Feb 2026
1 Month active

Languages Used

C++Markdown

Technical Skills

C++ developmentSQLTestingdocumentationunit testing

pytorch/torchtune

Oct 2024 Oct 2024
1 Month active

Languages Used

PythonYAML

Technical Skills

PyTorchconfiguration managementmachine learningmodel evaluation

mathworks/arrow

Nov 2024 Nov 2024
1 Month active

Languages Used

C++

Technical Skills

API DevelopmentC++Software Maintenance

apache/incubator-gluten

Feb 2026 Feb 2026
1 Month active

Languages Used

Java

Technical Skills

Javaconcurrent programmingunit testing

IBM/velox

Feb 2026 Feb 2026
1 Month active

Languages Used

C++Python

Technical Skills

C++ developmentSQLdata processingunit testing