Gungun Raut completed Machine Learning for Automotive Safety

Built a perception-validation dossier that correctly defined detection via IoU, computed precision/recall and VRU false-negative rate from a scored table, and then stress-tested VRU recall across operating conditions. The work shows strong safety-minded evaluation discipline by surfacing the night, occluded, and rare-class failure modes that matter most for release decisions.

• Leakage-Free Detection Definition
• Honest Metric Evaluation
• Per-Condition Safety Analysis
• Risk-Based Triage