awslabs/graphstorm
Oct 2024 – Aug 2025
10 Months active
Languages Used
PythonRSTShellBashCJinja2rstDockerfile
Technical Skills
Cloud ComputingData EngineeringDocumentationEvaluation MetricsFile SystemsGraph Neural Networks
Theodore Vasiloudis
PROFILE
Theodore Vasiloudis
Thanos Vasiloudis contributed to the awslabs/graphstorm repository by engineering robust, production-ready features for distributed graph machine learning on AWS. Over ten months, he delivered end-to-end solutions for data processing, deployment automation, and model evaluation, focusing on scalable workflows and reproducibility. Thanos implemented SageMaker integration, Docker-based development environments, and advanced configuration management, using Python, Bash, and Apache Spark to streamline data transformation and model training pipelines. His work addressed deployment stability, data integrity, and flexible input handling, while enhancing documentation and observability. The depth of his contributions reflects strong backend engineering and a comprehensive understanding of cloud-based MLOps challenges.
Overall Statistics
Feature vs Bugs
74%Features
Repository Contributions
56Total
Bugs
9
Commits
56
Features
26
Lines of code
17,230
Activity Months10
Your Network
1388 people
Work History
August 2025
5 Commits • 3 Features
Aug 1, 2025August 2025 monthly performance summary for awslabs/graphstorm. Focused on delivering distributed graph processing improvements, safer config handling, release packaging optimizations, and enhanced deployment flexibility for real-time in VPC.
5 Commits • 3 Features
Aug 1, 2025August 2025 monthly performance summary for awslabs/graphstorm. Focused on delivering distributed graph processing improvements, safer config handling, release packaging optimizations, and enhanced deployment flexibility for real-time in VPC.
August 2025
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025: Enhanced observability for GraphStorm's data loading path through non-breaking logging and documentation improvements to get_node_infer_set, improving diagnostics without altering behavior.
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025: Enhanced observability for GraphStorm's data loading path through non-breaking logging and documentation improvements to get_node_infer_set, improving diagnostics without altering behavior.
May 2025
7 Commits • 4 Features
May 1, 2025May 2025 summary for awslabs/graphstorm: Delivered enhancements to improve testing, input flexibility, docs, and deployment readiness. Key outcomes include: SageMaker integration improvements with optional CPU image provisioning and switch to SageMaker local mode to simplify local testing and multi-instance execution; GSProcessing received wildcard (*) support for input file paths to support flexible local and S3 data patterns; Documentation improvements enhanced onboarding and guidance, including environment setup and FocalLoss messaging; Packaging and environment updates updated the processing package to 0.4.2 and added Dockerfiles for EMR and SageMaker to streamline deployments. These changes reduce setup friction, accelerate local testing, and enable smoother deployments across AWS ML environments.
7 Commits • 4 Features
May 1, 2025May 2025 summary for awslabs/graphstorm: Delivered enhancements to improve testing, input flexibility, docs, and deployment readiness. Key outcomes include: SageMaker integration improvements with optional CPU image provisioning and switch to SageMaker local mode to simplify local testing and multi-instance execution; GSProcessing received wildcard (*) support for input file paths to support flexible local and S3 data patterns; Documentation improvements enhanced onboarding and guidance, including environment setup and FocalLoss messaging; Packaging and environment updates updated the processing package to 0.4.2 and added Dockerfiles for EMR and SageMaker to streamline deployments. These changes reduce setup friction, accelerate local testing, and enable smoother deployments across AWS ML environments.
May 2025
April 2025
6 Commits • 3 Features
Apr 1, 2025April 2025 (2025-04) focused on stability, correctness, and expanded deployment/readiness for GraphStorm. Delivered core stability improvements with refactored no-op transformation, better docs and test separation, enhanced parsing documentation, corrected binary classification focal loss handling for binary setups, and strengthened per-type node validation in random partitioning. Expanded model-tuning and inference capabilities with SageMaker HyperBand support and all-target-node inference, complemented by navigable documentation improvements to streamline adoption. The combined effort reduces defects, accelerates experimentation, and broadens production readiness for more complex workloads.
April 2025
6 Commits • 3 Features
Apr 1, 2025April 2025 (2025-04) focused on stability, correctness, and expanded deployment/readiness for GraphStorm. Delivered core stability improvements with refactored no-op transformation, better docs and test separation, enhanced parsing documentation, corrected binary classification focal loss handling for binary setups, and strengthened per-type node validation in random partitioning. Expanded model-tuning and inference capabilities with SageMaker HyperBand support and all-target-node inference, complemented by navigable documentation improvements to streamline adoption. The combined effort reduces defects, accelerates experimentation, and broadens production readiness for more complex workloads.
March 2025
8 Commits • 6 Features
Mar 1, 2025March 2025 monthly summary focused on automation, data-processing robustness, and SageMaker integration across the GraphStorm repo. Delivered automation enhancements, improved data handling defaults, and strengthened deployment stability. Updated documentation to enable easier adoption and operation, while maintaining release discipline. Key outcomes in GraphStorm (awslabs/graphstorm): - Dynamic Docker image version detection for the push script to remove explicit poetry-based versioning and streamline deployments. - GConstruct defaults numerical transformations to mean imputation, improving handling of missing values across numerical transformations. - SageMaker integration improvements: corrected hostname modification library path to prevent preloading conflicts and boost HPO stability. - Expanded GraphStorm-SageMaker Pipelines documentation, covering setup, execution, configuration, and advanced usage to accelerate onboarding and integration. - GConstruct no-op transformations now support parsing strings of delimited numbers as vectors, with updated documentation and conversions to reflect enhanced behavior.
8 Commits • 6 Features
Mar 1, 2025March 2025 monthly summary focused on automation, data-processing robustness, and SageMaker integration across the GraphStorm repo. Delivered automation enhancements, improved data handling defaults, and strengthened deployment stability. Updated documentation to enable easier adoption and operation, while maintaining release discipline. Key outcomes in GraphStorm (awslabs/graphstorm): - Dynamic Docker image version detection for the push script to remove explicit poetry-based versioning and streamline deployments. - GConstruct defaults numerical transformations to mean imputation, improving handling of missing values across numerical transformations. - SageMaker integration improvements: corrected hostname modification library path to prevent preloading conflicts and boost HPO stability. - Expanded GraphStorm-SageMaker Pipelines documentation, covering setup, execution, configuration, and advanced usage to accelerate onboarding and integration. - GConstruct no-op transformations now support parsing strings of delimited numbers as vectors, with updated documentation and conversions to reflect enhanced behavior.
March 2025
February 2025
6 Commits • 2 Features
Feb 1, 2025February 2025 — Delivered substantial business value for GraphStorm: improved developer experience, data reliability, and scalable experimentation. Implemented Docker-based development/deployment enhancements (TensorBoard integration in images, optional ParMETIS, GSProcessing 0.4.1, and new EMR/EMR Serverless Dockerfiles with PyTorch upgrade). Added SageMaker HyperParameter Optimization support with launcher/training script integration for automated tuning. Enforced RFC 4180-compliant CSV parsing for DistHeterogeneousGraphLoader to improve data loading consistency with Pandas defaults. Fixed ID map overlapping IDs with partitioning fixes and tests to ensure data integrity. These changes reduce setup time, enable efficient experimentation, and improve data quality across pipelines.
February 2025
6 Commits • 2 Features
Feb 1, 2025February 2025 — Delivered substantial business value for GraphStorm: improved developer experience, data reliability, and scalable experimentation. Implemented Docker-based development/deployment enhancements (TensorBoard integration in images, optional ParMETIS, GSProcessing 0.4.1, and new EMR/EMR Serverless Dockerfiles with PyTorch upgrade). Added SageMaker HyperParameter Optimization support with launcher/training script integration for automated tuning. Enforced RFC 4180-compliant CSV parsing for DistHeterogeneousGraphLoader to improve data loading consistency with Pandas defaults. Fixed ID map overlapping IDs with partitioning fixes and tests to ensure data integrity. These changes reduce setup time, enable efficient experimentation, and improve data quality across pipelines.
January 2025
13 Commits • 2 Features
Jan 1, 2025January 2025 (Month 2025-01) highlights for the GraphStorm repository awslabs/graphstorm. Key features delivered include SageMaker integration and deployment tooling, enabling GraphStorm pipeline creation and execution on SageMaker with automation scripts, documentation, and improved region handling and download strategies to streamline deployment and inference on AWS. Also delivered configuration and input-handling enhancements for GSProcessing and GConstruct, standardizing custom split configuration, enabling directory inputs, and expanding config conversion to support standard transforms with scalable label transformation using Spark. Major bug fixes address data integrity and training data handling: ParquetRowCounter fix to prevent cross-type feature name overwriting, enforced re-ordering during node label processing, and improved training config messaging. Build system and packaging improvements stabilize the workflow by constraining poetry-core versions (< 2.0.0) and removing Poetry as a build dependency for GraphStorm Processing images, with an updated EMRS image as needed. Overall impact includes faster, more reliable AWS deployments and in-production inferences, improved data integrity for training data, and stronger packaging stability. Demonstrated technologies and skills: SageMaker Pipelines, AWS config precedence handling, GConstruct/GSProcessing architecture, Spark-based label transformations, Parquet IO/data integrity practices, Python packaging and build tooling (poetry-core constraints), and EMR image management.
13 Commits • 2 Features
Jan 1, 2025January 2025 (Month 2025-01) highlights for the GraphStorm repository awslabs/graphstorm. Key features delivered include SageMaker integration and deployment tooling, enabling GraphStorm pipeline creation and execution on SageMaker with automation scripts, documentation, and improved region handling and download strategies to streamline deployment and inference on AWS. Also delivered configuration and input-handling enhancements for GSProcessing and GConstruct, standardizing custom split configuration, enabling directory inputs, and expanding config conversion to support standard transforms with scalable label transformation using Spark. Major bug fixes address data integrity and training data handling: ParquetRowCounter fix to prevent cross-type feature name overwriting, enforced re-ordering during node label processing, and improved training config messaging. Build system and packaging improvements stabilize the workflow by constraining poetry-core versions (< 2.0.0) and removing Poetry as a build dependency for GraphStorm Processing images, with an updated EMRS image as needed. Overall impact includes faster, more reliable AWS deployments and in-production inferences, improved data integrity for training data, and stronger packaging stability. Demonstrated technologies and skills: SageMaker Pipelines, AWS config precedence handling, GConstruct/GSProcessing architecture, Spark-based label transformations, Parquet IO/data integrity practices, Python packaging and build tooling (poetry-core constraints), and EMR image management.
January 2025
December 2024
3 Commits • 2 Features
Dec 1, 2024December 2024 Monthly Summary for awslabs/graphstorm focusing on deployment stability, tooling improvements, and SageMaker integration.
December 2024
3 Commits • 2 Features
Dec 1, 2024December 2024 Monthly Summary for awslabs/graphstorm focusing on deployment stability, tooling improvements, and SageMaker integration.
November 2024
4 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for awslabs/graphstorm: Delivered key features and bug fixes that strengthen SageMaker deployment, data processing reliability, and reproducibility of transformations. Focused on business value: streamlined model deployment on SageMaker, robust data ingestion, and consistent data transformations with GSProcessing.
4 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for awslabs/graphstorm: Delivered key features and bug fixes that strengthen SageMaker deployment, data processing reliability, and reproducibility of transformations. Focused on business value: streamlined model deployment on SageMaker, robust data ingestion, and consistent data transformations with GSProcessing.
November 2024
October 2024
3 Commits • 1 Features
Oct 1, 2024Summary for 2024-10: Delivered two parallel improvements that add business value and reliability to graphstorm. 1) Introduced Adjusted Mean Ranking Index (AMRI) for Link Prediction, including evaluation changes to return candidate list sizes and supporting docs/config updates (commits 993a71f55ab0c89a18994d717c43fd3ae0f8374c and ee16e74cf180932687092c9b4478d9a2fc8214f7). 2) Fixed Edge Feature Path Normalization for EFS Compatibility by replacing colons with underscores in edge feature paths (commit ed0f6986d83bd11a88a013ba79cc3635cf0061f5). These changes improve model evaluation fidelity, storage reliability, and developer onboarding.
October 2024
3 Commits • 1 Features
Oct 1, 2024Summary for 2024-10: Delivered two parallel improvements that add business value and reliability to graphstorm. 1) Introduced Adjusted Mean Ranking Index (AMRI) for Link Prediction, including evaluation changes to return candidate list sizes and supporting docs/config updates (commits 993a71f55ab0c89a18994d717c43fd3ae0f8374c and ee16e74cf180932687092c9b4478d9a2fc8214f7). 2) Fixed Edge Feature Path Normalization for EFS Compatibility by replacing colons with underscores in edge feature paths (commit ed0f6986d83bd11a88a013ba79cc3635cf0061f5). These changes improve model evaluation fidelity, storage reliability, and developer onboarding.
Activity
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Quality Metrics
Correctness92.0%
Maintainability87.8%
Architecture88.8%
Performance84.2%
AI Usage23.6%
Skills & Technologies
Programming Languages
BashCDockerfileJinja2MarkdownPytestPythonRSTShellTOML
Technical Skills
AI-assisted DevelopmentAWSAWS CLIAWS S3AWS SageMakerAlgorithm ImplementationApache SparkBackend DevelopmentBash ScriptingBinary ClassificationBug FixingBuild AutomationBuild SystemsCI/CDCLI Development
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