pasteurlabs/tesseract-core
Mar 2025 – Mar 2026
5 Months active
Languages Used
MarkdownPythonYAML
Technical Skills
API DevelopmentMachine LearningPyTorchPythonTesseractFEM simulation
Andrin Rehmann
PROFILE
Andrin Rehmann
Contributed to the pasteurlabs/tesseract-core repository by developing advanced features for machine learning-enabled OCR, shape optimization, and automatic differentiation workflows. Leveraged Python, PyTorch, and Docker to implement reproducible ML pipelines, differentiable FEM simulations, and memory-constrained container deployments. Enhanced the SDK’s performance by optimizing serialization formats and introduced experimental autodiff endpoint derivation helpers to expand gradient computation capabilities. Delivered comprehensive documentation, onboarding improvements, and rigorous unit and end-to-end testing using Jupyter Notebooks and pytest. The work emphasized cross-tool integration, collaborative development, and performance optimization, enabling teams to accelerate research, streamline onboarding, and automate complex simulation and optimization tasks.
Overall Statistics
Feature vs Bugs
86%Features
Repository Contributions
7Total
Bugs
1
Commits
7
Features
6
Lines of code
7,784
Activity Months5
Your Network
14 peopleWork History
March 2026
1 Commits • 1 Features
Mar 1, 2026Concise monthly summary for 2026-03 focusing on delivering enhanced autodiff capabilities in the tesseract-core repository and validating them with comprehensive tests and end-to-end examples.
1 Commits • 1 Features
Mar 1, 2026Concise monthly summary for 2026-03 focusing on delivering enhanced autodiff capabilities in the tesseract-core repository and validating them with comprehensive tests and end-to-end examples.
March 2026
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for pasteurlabs/tesseract-core: Delivered a Docker memory limit feature enabling per-container memory constraints via CLI (--memory on run/serve) and Python API (memory arg for Tesseract.from_image). This improvement ensures better resource management and reduces OOM risk in multi-container deployments. The default behavior remains unlimited memory when not specified.
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for pasteurlabs/tesseract-core: Delivered a Docker memory limit feature enabling per-container memory constraints via CLI (--memory on run/serve) and Python API (memory arg for Tesseract.from_image). This improvement ensures better resource management and reduces OOM risk in multi-container deployments. The default behavior remains unlimited memory when not specified.
December 2025
3 Commits • 2 Features
Dec 1, 2025Month: 2025-12 — Concise monthly summary highlighting business value and technical achievements for pasteurlabs/tesseract-core. Delivered an open-source shape optimization workflow using JAX-FEM (for generating 3D bar geometries and their signed distance fields) to provide an in-house, open alternative to proprietary tooling. Implemented a major SDK performance improvement by changing the default output format to json+base64 (dropping json+binref), resulting in substantial serialization speedups. Performed targeted documentation enhancements to clarify build command naming and onboarding. This period also included CI/test alignment and collaborative contributions.
3 Commits • 2 Features
Dec 1, 2025Month: 2025-12 — Concise monthly summary highlighting business value and technical achievements for pasteurlabs/tesseract-core. Delivered an open-source shape optimization workflow using JAX-FEM (for generating 3D bar geometries and their signed distance fields) to provide an in-house, open alternative to proprietary tooling. Implemented a major SDK performance improvement by changing the default output format to json+base64 (dropping json+binref), resulting in substantial serialization speedups. Performed targeted documentation enhancements to clarify build command naming and onboarding. This period also included CI/test alignment and collaborative contributions.
December 2025
November 2025
1 Commits • 1 Features
Nov 1, 2025Month: 2025-11 — Focused on delivering developer-facing capabilities to enable parametric shape optimization workflows by integrating Ansys with Tesseract. Delivered documentation and example scripts demonstrating a differentiable FEM-based optimization workflow, enabling teams to explore parametric shapes with real-time feedback. This work improves cross-tool collaboration, reduces integration risk, and accelerates design exploration for complex simulations. No major bugs fixed this month; maintenance tasks centered on enhancing documentation quality, ensuring CI readiness, and stabilizing the new workflow for team-wide adoption. Overall, the effort drives faster time-to-value for advanced optimization scenarios and establishes a foundation for further automation and testing of optimization workflows. Technologies/skills demonstrated include Python scripting for examples, documentation tooling, cross-tool integration between Ansys and Tesseract, differentiable FEM concepts, and collaborative documentation practices.
November 2025
1 Commits • 1 Features
Nov 1, 2025Month: 2025-11 — Focused on delivering developer-facing capabilities to enable parametric shape optimization workflows by integrating Ansys with Tesseract. Delivered documentation and example scripts demonstrating a differentiable FEM-based optimization workflow, enabling teams to explore parametric shapes with real-time feedback. This work improves cross-tool collaboration, reduces integration risk, and accelerates design exploration for complex simulations. No major bugs fixed this month; maintenance tasks centered on enhancing documentation quality, ensuring CI readiness, and stabilizing the new workflow for team-wide adoption. Overall, the effort drives faster time-to-value for advanced optimization scenarios and establishes a foundation for further automation and testing of optimization workflows. Technologies/skills demonstrated include Python scripting for examples, documentation tooling, cross-tool integration between Ansys and Tesseract, differentiable FEM concepts, and collaborative documentation practices.
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for pasteurlabs/tesseract-core: Delivered a PyTorch-based vector add/sub example for Tesseract and established an onboarding-friendly, reproducible ML workflow. Implemented the vectoradd_torch example with README, API definition, configuration, and requirements, demonstrating vector addition/subtraction using PyTorch with automatic differentiation. This release includes a PyTorch initialization template to streamline experiments and aligns with the team's focus on ML-enabled OCR capabilities.
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for pasteurlabs/tesseract-core: Delivered a PyTorch-based vector add/sub example for Tesseract and established an onboarding-friendly, reproducible ML workflow. Implemented the vectoradd_torch example with README, API definition, configuration, and requirements, demonstrating vector addition/subtraction using PyTorch with automatic differentiation. This release includes a PyTorch initialization template to streamline experiments and aligns with the team's focus on ML-enabled OCR capabilities.
March 2025
Activity
Loading activity data...
Quality Metrics
Correctness94.4%
Maintainability88.6%
Architecture88.6%
Performance85.8%
AI Usage37.2%
Skills & Technologies
Programming Languages
MarkdownPythonYAML
Technical Skills
3D ModelingAPI DevelopmentCLI DevelopmentData VisualizationDockerFEM simulationFinite Element AnalysisJupyter NotebookMachine LearningPerformance OptimizationPyTorchPythonPython ProgrammingSDK DevelopmentTesseract
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline