Shubham Ahuja completed Machine Learning for Automotive Safety

Built a perception validation dossier end to end for a fictional Aurora-7 detector: defined the IoU-based detection rule, computed precision/recall and VRU false-negative rate from a synthetic scored table, and sliced recall by lighting, visibility, and class to surface the highest-risk night and occlusion failures. Closed the loop with ISO 21448 SOTIF chains, a condition-limited ship recommendation, and a real-world comparison to the Uber Tempe crash.

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