Stefano Pini is a Machine Learning Engineer with nine years' experience specializing in prediction and planning for autonomous driving, currently at Wayve after roles at Woven Planet UK (formerly Lyft Level 5). He holds a PhD in Computer Engineering and Science, with a research background in computer vision and deep learning for human-vehicle interaction. Stefano blends research rigor with production-focused engineering, having improved closed-loop planning evaluation, metrics, and visualizations in the widely used L5Kit repository and integrated multimodal models like SafePathNet into practical examples. Based in Stony Stratford, he brings a strong track record of turning academic advances into reproducible tooling and clear documentation that help bridge simulation and real-world driving stacks.
Contributions:11 reviews, 12 commits, 20 PRs in 1 year 9 months
Contributions summary:Stefano focused on updating and enhancing the closed-loop evaluation process within the L5Kit repository, specifically within the context of planning tasks. The user modified and extended the `examples/planning/closed_loop_test.ipynb` notebook to incorporate new metrics for closed-loop evaluation, including code for metrics to assess performance such as displacement error and collision detection. They also made improvements to documentation and visualizations within the notebook. The user also integrated SafePathNet, a multimodal prediction model, and incorporated it into the documentation and examples, demonstrating experience with model implementation.
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