Mr Mehdi Hosseinzadeh
Grant-Funded Research Fellow
School of Computer Science and Information Technology
College of Engineering and Information Technology
Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.
As a Research Fellow at the Australian Institute for Machine Learning, Mehdi contributes to projects at the intersection of Computer Vision, Machine Learning, and Robotics. His current focus lies in harnessing self-supervised multi-modal learning for advancements in robotics and autonomous system. With a background in Geometry, Visual SLAM, 3D Reconstruction, and Multi-Modal Learning, his aim is to merge theoretical research with practical applications.He earned his PhD from the University of Adelaide, where he was affiliated with the Australian Centre for Robotic Vision for Machine Learning. During his doctoral studies, Mehdi specialised in real-time structure and object-aware semantic visual SLAM. He tackled the challenges inherent in traditional geometric SLAM frameworks by integrating deep-learned rich priors derived from advanced 3D scene understanding. For more information about SLAM and his work, refer to: https://www.adelaide.edu.au/aiml/our-research/robotic-vision/simultaneous-localisation-and-mapping-slam
| Date | Role | Research Topic | Program | Degree Type | Student Load | Student Name |
|---|---|---|---|---|---|---|
| 2026 | Co-Supervisor | Run-Time Monitoring of Machine Learning for Robotic and Autonomous Perception | Doctor of Philosophy | Doctorate | Full Time | Mr One il Chiang |
| Date | Role | Research Topic | Location | Program | Supervision Type | Student Load | Student Name |
|---|---|---|---|---|---|---|---|
| 2025 - 2026 | Principal Supervisor | Object-Based Visual SLAM for Urban Tram Systems | The University of Adelaide | Master Of Artificial Intelligence and Machine Learning | Master | Full Time | Phuong Quoc Anh To |
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