Khaled Saleh
Hi, I’m Khaled Saleh, a Computer Vision researcher and engineer based in Sydney, Australia, with 10+ years of hands-on experience designing, developing, and deploying vision-based AI/ML systems for autonomous vehicles,…
About
Hi, I’m Khaled Saleh, a Computer Vision researcher and engineer based in Sydney, Australia, with 10+ years of hands-on experience designing, developing, and deploying vision-based AI/ML systems for autonomous vehicles, robotics, and real-world perception tasks. I enjoy solving complex perception problems end-to-end, from research ideas to production-grade deployments, and collaborating with cross-disciplinary teams to deliver robust, real-world solutions.
I specialize in deep learning for computer vision, including object detection, pose and trajectory prediction, 3D point cloud processing, and thermal imagery analysis, using Python, C/C++, OpenCV, PyTorch, and TensorFlow. I’m passionate about taking CV algorithms from research to production, building scalable perception pipelines, and continuously learning to tackle new sensing modalities and real-world constraints.
- 14 years' experience
- Joined December 2025
Languages
- EnglishFluent
Industry experience
- Education
- Government
- Healthcare
- Computers & Electronics
- Transportation & Logistics
- Professional Services
- Software & Internet
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Work experience· 12 roles
Developed and deployed a real-time camera-based contamination detection system for an industrial bio-waste processing company, building the end-to-end pipeline with PyTorch and OpenCV, including a real-time object detection model, inference service, and an operations dashboard with an alerting system for non-compliance events. Led an applied research project on LLM and multimodal perception for safety hazard detection on construction sites, combining vision-based hazard recognition with LLM-based reasoning to produce contextual safety alerts, implemented using PyTorch, HuggingFace Transformers, and OpenCV.
Led design and delivery of AI-driven solutions for the public sector and educational content enhancement; directed teaching and curriculum development for AI, Data Science, and Computing/IT.
Designed end-to-end spatio-temporal CNNs (PyTorch) for video-based human engagement and behaviour detection in human-robot interaction settings. Built VoxelScape, a large-scale simulated 3D point cloud dataset for training LiDAR-based perception models for urban traffic environments.
Education
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