
Rongcheng Wu
@rongchengwu
I build production industrial computer vision and edge AI systems for 3D inspection and safety.
What I'm looking for
At Zabidou, I build production machine-vision systems for industrial inspection, combining NVIDIA Jetson deployment, 3D point-cloud reconstruction, line-scan laser sensing, object tracking, and anomaly detection.
At the University of Technology Sydney, I engineered industrial CV systems from data capture through deployed services, including six-stream worker-safety analytics, 30+ FPS edge inference, and stereo-vision pipelines. I also built production monitoring workflows with telemetry, alerting, failure recovery, and stakeholder reporting.
I develop practical 3D and edge-vision pipelines, from camera and sensor calibration through model evaluation, TensorRT/ONNX optimisation, and field deployment. My projects include Jetson point-cloud reconstruction, real-time production-line inspection, laser 3D measurement, and on-device livestock tracking.
My depth and stereo work is backed by first-author publications in AAAI and IJCV. I also bring data-engineering experience from Charles Darwin University, where I built Power Automate workflows and dbt/SQL pipelines for governed reporting and operational analytics.
Experience
Work history, roles, and key accomplishments
Computer Vision Engineer / Machine Learning Engineer
Zabidou
Mar 2026 - Sep 2026 (6 months)
Building production machine-vision systems for industrial inspection, including NVIDIA Jetson edge deployment, 3D point-cloud reconstruction, line-scan laser/depth sensing, and production-line object tracking/anomaly detection. Owns camera/sensor integration, calibration, model training, runtime optimization, and field-ready reporting.
Research Engineer – Industrial Computer Vision
University of Technology Sydney
Sep 2021 - Mar 2026 (4 years 6 months)
Engineered industrial CV systems from data capture to deployed services, including 6-RTSP-stream worker-safety analytics, 30+ FPS edge inference, and 3D/stereo vision pipelines. Built reliable production workflows around camera streams, model evaluation, service/edge deployment, telemetry, alerting, and stakeholder-facing reporting.
Research Data Engineer – Workflow Automation and Analytics
Charles Darwin University
Jun 2025 - Dec 2025 (6 months)
Built automated operational workflows with Power Automate and data-engineering pipelines with dbt/SQL, covering ingestion, transformation, validation, refresh scheduling, and Power BI reporting. Applied deep learning models to healthcare analytics research, including data preprocessing, model training, and manuscript preparation.
Education
Degrees, certifications, and relevant coursework
University of Technology Sydney
PhD, AI and Data Science
2022 - 2026
PhD in AI and Data Science (Industry PhD) from the University of Technology Sydney, completed in March 2026.
University of New South Wales
Master of Philosophy, Computer Science
2020 - 2022
Master of Philosophy in Computer Science from the University of New South Wales, completed in 2022.
Availability
Location
Authorized to work in
Salary expectations
Social media
Skills
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