Saina Ali completed Machine Learning for Automotive Safety

Built a complete perception-validation dossier for a fictional Aurora-7 detector: defined IoU-based detection correctly, scored precision/recall and the VRU false-negative rate from a synthetic detections table, and then sliced recall by lighting, visibility, and class to expose the night and occlusion failure modes. The final recommendation was evidence-based and internally consistent, with ISO 21448 SOTIF chains and concrete mitigations tied directly to the measured weaknesses.

• Leakage-Free Detection Definition
• Safety-Critical Metric Selection
• Per-Condition Failure Triage
• SOTIF Functional-Insufficiency Reasoning