
Paul contributed to the ScrollPrize/villa repository over six months, delivering nine features and resolving critical bugs across machine learning and 3D reconstruction workflows. He integrated Weights & Biases for experiment tracking, enhanced fiber tracing pipelines with robust direction extraction and Zarr-backed storage, and developed end-to-end evaluation tooling for surface tracers. Using C++, Python, and PyTorch, Paul optimized neural tracing algorithms, improved batch processing, and strengthened code maintainability through targeted refactoring and documentation. His work addressed reliability and scalability, introducing batch signaling for UI efficiency and robust input handling, resulting in more reproducible experiments and streamlined data processing across the codebase.
January 2026: ScrollPrize/villa — Delivered major neural tracer enhancements for VC3D and associated maintenance. Implemented improved direction finding and neighbor selection in the neural tracer, added bootstrapping support (pre_neural_generations=0), and optimized batch construction in GrowPatch. Performed code cleanup (e.g., removal of unused slots in trace.py) and expanded evaluation tooling, including an evaluation script for neural traces within vc_grow_seg_from_seed and clearer patch naming. These changes improve accuracy, reliability, and experimentation throughput, streamline maintenance, and prepare VC3D workflows for broader adoption. Notable commits reflected in this work: b0f2507dbebf8fddf798e8bd7beba873e4f80633; ed694710445676987992ac2b740000458ad3ae04.
January 2026: ScrollPrize/villa — Delivered major neural tracer enhancements for VC3D and associated maintenance. Implemented improved direction finding and neighbor selection in the neural tracer, added bootstrapping support (pre_neural_generations=0), and optimized batch construction in GrowPatch. Performed code cleanup (e.g., removal of unused slots in trace.py) and expanded evaluation tooling, including an evaluation script for neural traces within vc_grow_seg_from_seed and clearer patch naming. These changes improve accuracy, reliability, and experimentation throughput, streamline maintenance, and prepare VC3D workflows for broader adoption. Notable commits reflected in this work: b0f2507dbebf8fddf798e8bd7beba873e4f80633; ed694710445676987992ac2b740000458ad3ae04.
December 2025: Stability and reliability improvements for ScrollPrize/villa's neural tracing cropping workflow. Implemented a robust bug fix that rounds the min_corner to the nearest integer to handle non-integer inputs, preventing errors and improving overall pipeline reliability. The change was implemented in commit 3484ab7ae02b31736e00b97276985f391212b467 and aligns with our goal of reducing edge-case failures, improving data quality, and lowering operational risk in production.
December 2025: Stability and reliability improvements for ScrollPrize/villa's neural tracing cropping workflow. Implemented a robust bug fix that rounds the min_corner to the nearest integer to handle non-integer inputs, preventing errors and improving overall pipeline reliability. The change was implemented in commit 3484ab7ae02b31736e00b97276985f391212b467 and aligns with our goal of reducing edge-case failures, improving data quality, and lowering operational risk in production.
Month 2025-11: Delivered batch signaling for VCCollection to report multiple collections added at once (collectionsAdded), enabling efficient UI updates and improved performance during large collection changes. Refactored signaling and loadJSON path to minimize unnecessary updates by signaling only collection-level changes, reducing render churn. No major bugs fixed this month. Impact: smoother UI for large datasets, lower CPU time during updates, and clearer telemetry through commit traceability.
Month 2025-11: Delivered batch signaling for VCCollection to report multiple collections added at once (collectionsAdded), enabling efficient UI updates and improved performance during large collection changes. Refactored signaling and loadJSON path to minimize unnecessary updates by signaling only collection-level changes, reducing render churn. No major bugs fixed this month. Impact: smoother UI for large datasets, lower CPU time during updates, and clearer telemetry through commit traceability.
September 2025: Delivered end-to-end evaluation tooling for ScrollPrize/villa surface tracers, strengthened metric semantics, and expanded analysis capabilities with targeted z-range support and seed management. Implemented robust input handling to improve reliability and prevent crashes, and enhanced documentation and configuration for reproducible experiments with WandB integration.
September 2025: Delivered end-to-end evaluation tooling for ScrollPrize/villa surface tracers, strengthened metric semantics, and expanded analysis capabilities with targeted z-range support and seed management. Implemented robust input handling to improve reliability and prevent crashes, and enhanced documentation and configuration for reproducible experiments with WandB integration.
August 2025 – ScrollPrize/villa: Focused on delivering precise fiber tracing and direction infrastructure to unlock more accurate analyses, scalable data pipelines, and maintainable code. Achievements include robust Patch Tracing and GrowPatch enhancements with multi-field fiber direction support, plus a forward-looking fiber direction extraction pipeline with Zarr-backed storage. These changes improve accuracy of fiber tracing, enable richer direction data for downstream models, and reduce maintenance overhead while supporting scalable data workflows.
August 2025 – ScrollPrize/villa: Focused on delivering precise fiber tracing and direction infrastructure to unlock more accurate analyses, scalable data pipelines, and maintainable code. Achievements include robust Patch Tracing and GrowPatch enhancements with multi-field fiber direction support, plus a forward-looking fiber direction extraction pipeline with Zarr-backed storage. These changes improve accuracy of fiber tracing, enable richer direction data for downstream models, and reduce maintenance overhead while supporting scalable data workflows.
July 2025 (2025-07) focused on improving ML experiment observability and reproducibility by introducing Weights & Biases logging into the model training workflow for ScrollPrize/villa. The integration enables tracking of training metrics, hyperparameters, configurations, and artifacts across runs, empowering data-driven iteration and faster debugging. This work is anchored by the commit adding wandb logging in vesuvius.models trainer.
July 2025 (2025-07) focused on improving ML experiment observability and reproducibility by introducing Weights & Biases logging into the model training workflow for ScrollPrize/villa. The integration enables tracking of training metrics, hyperparameters, configurations, and artifacts across runs, empowering data-driven iteration and faster debugging. This work is anchored by the commit adding wandb logging in vesuvius.models trainer.

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