Dinan Jayasinghe completed Machine Learning for Automotive Safety

Built a perception validation dossier end to end for a synthetic Aurora-7 detector: defined detection correctly with an IoU >= 0.5 match rule, computed precision/recall and the VRU false-negative rate, and then sliced recall by lighting, visibility, and class to expose the dangerous night and occluded VRU failures. The final safety case framed these as ISO 21448 functional insufficiencies and closed with an evidence-based GO-WITH-CONDITIONS recommendation tied to the dossier’s own numbers.

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