Hari Mahajan completed Machine Learning for Automotive Safety

Built a perception validation dossier end to end for a synthetic Aurora-7 detector: defined detections with an IoU>=0.5 match rule, computed precision/recall plus the VRU false-negative rate, and sliced recall by lighting, visibility, and rarity to expose the night/occluded pedestrian risk. The final safety case tied those numbers to ISO 21448-style functional insufficiencies and produced an evidence-based ship verdict grounded in the student’s own metrics and the Tempe crash analysis.

• Leakage-Free Metric Definition
• Safety-Critical Slice Analysis
• ISO 21448 SOTIF Reasoning
• Evidence-Based Release Verdict