Dr Jasmin Martin is a lecturer in the School of Mechanical and Mining Engineering at the University of Queensland, where she teaches courses such as METR6203. Her email address is publicly listed as jasmin.martin@uq.edu.au in course profiles and research papers. She completed her Doctor of Philosophy at Queensland University of Technology. Previously, she held the position of Research Fellow in the Faculty of Engineering, School of Electrical Engineering and Robotics at Queensland University of Technology. Her research interests include artificial intelligence and electrical engineering. Martin's scholarly output focuses on vision-based technologies for unmanned aircraft systems, Bayesian quickest change detection methods, and applications in autonomous mining operations. She is affiliated with the University of Queensland on her Google Scholar profile, with a verified email at uq.edu.au.

Key publications by Jasmin Martin (often listed as J. James or J. Martin) include 'Learning to Detect Aircraft for Long-Range Vision-Based Sense-and-Avoid Systems' by J James, JJ Ford, and TL Molloy in IEEE Robotics and Automation Letters (2018); 'Below Horizon Aircraft Detection Using Deep Learning for Vision-Based Sense and Avoid' by J James, JJ Ford, and TL Molloy at the 2019 International Conference on Unmanned Aircraft Systems; 'Quickest Detection of Intermittent Signals with Application to Vision-Based Aircraft Detection' by J James, JJ Ford, and TL Molloy in IEEE Transactions on Control Systems Technology (2018); 'Exactly Optimal Bayesian Quickest Change Detection for Hidden Markov Models' by JJ Ford, J James, and TL Molloy in Automatica (2023); 'A Dataset of Stationary, Fixed-Wing Aircraft on a Collision Course for Vision-Based Sense and Avoid' by J Martin, J Riseley, and JJ Ford at the 2022 International Conference on Unmanned Aircraft Systems; 'On the Informativeness of Measurements in Shiryaev’s Bayesian Quickest Change Detection' by JJ Ford, J James, and TL Molloy in Automatica (2020); 'Change Detection for Undermodelled Processes Using Mismatched Hidden Markov Model Test Filters' by J James, JJ Ford, and TL Molloy in IEEE Control Systems Letters (2017); 'A Framework for Bayesian Quickest Change Detection in General Dependent Stochastic Processes' by J James, JJ Ford, and TL Molloy in IEEE Control Systems Letters (2024); 'Real-Time Dynamic Terrain Mapping for Autonomous Mining Operations' by V Bhandari, J James, T D’Adamo, T Phillips, and PR McAree in IEEE Transactions on Field Robotics (2025); and 'Comparison of Elastic Configurations for Energy Efficient Legged Locomotion' by J James, P Ross, and D Ball at the Australasian Conference on Robotics and Automation (2015). These works highlight her contributions to sense-and-avoid systems, signal processing for detection, and terrain mapping. She collaborates frequently with JJ Ford, TL Molloy, and others from UQ and QUT.

Professional Email: jasmin.martin@uq.edu.au