SOURCE NOTE / CANDIDATE / 2025 – Present

Shanghai Ben’an Intelligent · Research Engineer, Driver State Monitoring (DMS)

Deployed and validated real-time on-device driver-state monitoring, connecting safety-relevant alerts, low-power edge inference, and replay-driven validation. Deployed and validated eight safety-relevant detector classes: eye closure, yawning, distraction, phone use, smoking, face loss, lens occlusion, and eye anomaly. Shipped a 616-test pytest suite with replay-driven regressions, inference-cadence checks, and per-detector coverage metrics alongside model development. Designed the alert state machine with hierarchical face-loss and lens-occlusion fallbacks. Speed, ignition, and gear gating suppress false alarms in non-driving states; persisted per-camera calibration profiles support fleet-grade traceability. Fit the model pipeline to the low-power CV181x edge SoC by tightening inference cadence and per-stage compute budgets. Validated end-to-end on real cabin video and built the lab CLI for shadow-mode hard-case capture, human review, and replay-based metric reporting.

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Role, period, and contribution supplied directly by Donald.