Jongseok Park completed Machine Learning for Automotive Safety

Built a perception validation dossier end to end for a synthetic Aurora-7 detector: defined detection correctly at IoU ≥ 0.5, scored precision/recall and VRU false-negative rate, then sliced recall by lighting, visibility, and class rarity to expose the dangerous night/occluded VRU failures. Closed with an ISO 21448-style safety case and an evidence-based daylight-only ship recommendation tied to the Tempe crash analysis.

• Leakage-Free Detection Definition
• Safety-Critical Metric Selection
• Per-Condition Failure Triage
• SOTIF Hazard Framing