Rate My Professor Umair Iqbal

Dr. Umair Iqbal serves as a Research Associate in the School of Engineering at the University of Newcastle, Australia. He holds a Doctor of Philosophy degree from the University of Wollongong. From November 2022 to August 2024, he worked as a Research Fellow at the SMART Infrastructure Facility, University of Wollongong, where he led applied AI industrial projects for the Telstra-UOW AIoT Hub, contributed to the SAEF AIoT research project by developing embedded AI for Antarctic environmental monitoring, managed computer vision and machine learning industrial project collaborations, pitched innovative AIoT solutions to industry partners, managed NVIDIA DLI workshop series on deep learning and computer vision, coordinated Python courses at undergraduate and postgraduate levels, and mentored students on AI, machine learning, and deep learning projects.

Umair Iqbal is recognized as an Applied Artificial Intelligence researcher with a primary specialization in Computer Vision. His academic interests encompass Artificial Intelligence of Things (AIoT), Deep Learning, Edge-Computing, Disaster Management, and applications in Civil Geotechnical Engineering. Proficient in advanced tools including TensorFlow, PyTorch, Keras, OpenCV, and NVIDIA's TAO Toolkit, DeepStream, TensorRT, and Jetson edge computers, he develops scalable end-to-end video analytics solutions. His current research addresses rock fall assessment problems in open mine pits using AI and computer vision technologies. As an official NVIDIA Deep Learning Institute (DLI) Ambassador at the University of Newcastle, he conducts certified workshops such as Fundamentals of Deep Learning, Computer Vision for Industrial Inspection, and Getting Started with Jetson Nano. His contributions extend to sectors including disaster recovery, water resource management, and waste management, leveraging AI for enhanced decision-making processes.

Notable publications include: "Automated Lithology Segmentation of 3D Point Clouds from Highwalls Using Deep Learning" in Remote Sensing (2025); "Smart Video Analytics Solution to Identify Urban Floodborne Objects" in Journal of Computing in Civil Engineering (2025); "A versatile synthetic data generation framework for crack detection" in Engineering Structures (2025); "Safety After Dark: A Privacy Compliant and Real-Time Edge Computing Intelligent Video Analytics for Safer Public Transportation" in Sensors (2024); "An End-to-End Artificial Intelligence of Things (AIoT) Solution for Protecting Pipeline Easements against External Interference-An Australian Use-Case" in Sensors (2024); and the book chapter "Emerging role of unmanned aerial vehicles (UAVs) for disaster management applications" (2022).