April 2026 monthly summary for volcengine/verl: Implemented compute_score timing instrumentation to measure reward score computation within AgentLoopMetrics, enabling bottleneck identification during training. Introduced per-sample timing via _compute_score using simple_timer, and added aggregation metrics: agent_loop/compute_score/min|max|mean and agent_loop/slowest/compute_score. Ensured backward compatibility with default compute_score=0.0 and no API changes. This work provides enhanced observability and a foundation for performance optimization during model training.

September 2025 monthly summary for microsoft/onnxscript: Key feature delivered: ONNX Graph Fusion Optimization for Conv-Affine and HardSwish; fusion rules implemented to combine Conv-Affine (Mul+Add) with HardSwish in ONNX graphs, reducing operation count and improving runtime performance. Change tracked in commit 821015a652c31381349c5ec7de62b8a21a0fe3cb, associated with PR #2472. Major bugs fixed: none reported this month. Overall impact: accelerated ONNXScript model inference, lower latency and resource usage through fusion-based optimization. Technologies/skills demonstrated: graph-level optimization design and implementation, fusion rule development, performance validation, and cross-repo collaboration.

August 2025: Delivered CUDA execution provider enhancements in microsoft/onnxruntime by adding the HardSwish operator and bf16 support for HardSigmoid, improving inference performance and data-type coverage on bf16-capable GPUs.