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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.…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.

Khaled Saleh

AI Engineer, Data Scientist, AI Strategy Consultant, +4

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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.…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.

Available to hire

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.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Senior Researcher and Academic at School of Computer and Information Sciences, University of Newcastle

August 1, 2022 - Present

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.

AI Solutions Lead and Lecturer at University of Newcastle

August 1, 2022 - Present

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.

Research Fellow at Faculty of Engineering and IT (FEIT), University of Technology Sydney (UTS)

February 1, 2020 - July 1, 2022

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.

AI/ML Research Fellow at UTS

February 1, 2020 - July 1, 2022

Led AI research projects in Computational Agent Behaviour Modelling, Human-Centred AI, and Human-Computer Interaction; developed and deployed ML models for public sector, logistics, and e-commerce.

Computer Vision Researcher (Remote) at Calumino

May 1, 2018 - September 1, 2020

Development, debugging, and diagnosing of computer vision algorithms in Python for commercial thermal imagery sensors. Designed and validated image processing pipelines (detection, tracking, activity recognition) for low-resolution thermal data, from prototype through to production deployment.

Computer Vision AI Consultant at Calumino

May 1, 2018 - September 1, 2020

Developed, debugged, and optimised computer vision algorithms in Python for thermal imagery sensors, enhancing system performance and accuracy.

Research Assistant and Research Fellow at IISRI, Deakin University

January 1, 2016 - January 1, 2020

Developed deep learning models for real-time pedestrian and cyclist intent prediction from RGB and 3D LiDAR data for autonomous ground vehicles. Implemented domain adaptation for vehicle detection from Bird’s-Eye-View LiDAR point clouds; built perception pipelines in PyTorch, TensorFlow, OpenCV, and PCL.

AI Research Fellow at Deakin University

January 1, 2016 - January 1, 2020

Designed and developed socially aware AI predictive models for trusted autonomous systems; implemented real-time automated decision-making systems for mining and the public sector.

Embedded Software Engineer (ADAS) at Valeo

August 1, 2014 - December 1, 2015

Embedded C/C++ software design and development for Advanced Driver-Assistance Systems (ADAS) including camera-based perception modules. Automotive software testing and validation under real-time and safety constraints.

Embedded Software Engineer (ADAS Focus) at Valeo

August 1, 2014 - December 1, 2015

Engineered and developed embedded C/C++ software for Advanced Driver-Assistance Systems (ADAS), contributing to enhanced vehicle safety features.

Co-founder and R&D Engineer at Mubser, LLC

June 1, 2013 - July 1, 2014

Designed and developed obstacle avoidance and recognition algorithms using 3D depth (RGB-D) sensors in C/C++ for a wearable assistive device for the visually impaired. Coordinated technical development efforts between software and hardware teams.

Co-founder and AI R&D Engineer at Mubser, LLC

June 1, 2012 - July 1, 2014

Co-founded a ML-driven startup focused on assistive technology; product featured in Forbes. Led technical development efforts, designing and implementing obstacle avoidance and recognition algorithms.