Adjunct Professor
Peyman Moghadam
Faculty of Engineering,
School of Electrical Engineering & Robotics
Biography
Peyman Moghadam is an Adjunct Professor within the Engineering Faculty at QUT and a Senior Principal Research Scientist at CSIRO. He has worked at leading international research organisations including Deutsche Telekom Laboratories in Germany and the Singapore-MIT Alliance for Research and Technology in Singapore, and in 2022 he was a Visiting Professor at ETH Zürich. His research focuses on self-supervised learning, embodied AI, and robotics. He has supervised many PhD, Master’s and Honours students, with several receiving awards and recognition for their research excellence. Professor Moghadam has led several large-scale multidisciplinary R&D projects and he has won numerous awards for his innovations including Julius Career award, National and Queensland iAward for Research and Development, the Lord Mayor’s Budding Entrepreneurs Award. He has also contributed to the international robotics and AI community through editorial and leadership roles, including Area Chair roles for RSS and AAAI, editorial board member for IEEE Transactions on Robotics and IEEE Transactions on Field Robotics, and Co-Chair of the IEEE RAS Robot Learning Technical Committee. He is a Senior Member of IEEE and an ACM Distinguished SpeakerPersonal details
Positions
- Adjunct Professor
Faculty of Engineering,
School of Electrical Engineering & Robotics
Keywords
Deep Learning, Robotics, Embodied Intelligence, Self-Supervised Learning, Hyperspectral Perception, Thermal Perception, Machine Learning, SLAM, Multi-modal Learning, 3D multimodal Perception
Research field
Artificial intelligence, Other engineering, Other information and computing sciences
Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2020
Qualifications
- PhD
Professional memberships and associations
For more information on Adjunct Prof Peyman Moghadam research activities visit website:
https://research.csiro.au/robotics/
We are currently seeking outstanding candidates to undertake PhD research in Deep Learning applied to Robotics visit website for more details:
https://research.csiro.au/robotics/work-with-us/undergrad-masters-and-phd-students/phds/
Experience
Research Areas
- Robotics, Computer Vision, Machine Learning, Deep Learning.
- Beyond visible Spectrum Perception (Hyperspectral, Thermal).
- Embodied Intelligence, Self-Supervised Learning, Continual Learning
Research applications include:
- Energy
- Agriculture
- Health/Sports
- Manufacturing
Publications
- Mohamed, S., Haghighat, M., Fernando, T., Sridharan, S., Fookes, C. & Moghadam, P. (2024). FactoFormer: Factorized Hyperspectral Transformers with Self-Supervised Pre-Training. IEEE Transactions on Geoscience and Remote Sensing, 62. https://eprints.qut.edu.au/245518
- Knights, J., Hausler, S., Sridharan, S., Fookes, C. & Moghadam, P. (2024). GeoAdapt: Self-Supervised Test-Time Adaptation in LiDAR Place Recognition Using Geometric Priors. IEEE Robotics and Automation Letters, 9(1), 915–922. https://eprints.qut.edu.au/245271
- Haghighat, M., Moghadam, P., Mohamed, S. & Koniusz, P. (2024). Pre-training with Random Orthogonal Projection Image Modeling. Proceedings of the Twelfth International Conference on Learning Representations (ICLR). https://eprints.qut.edu.au/246732
- Vidanapathirana, K., Moghadam, P., Sridharan, S. & Fookes, C. (2023). Spectral Geometric Verification: Re-Ranking Point Cloud Retrieval for Metric Localization. IEEE Robotics and Automation Letters, 8(5), 2494–2501. https://eprints.qut.edu.au/238892
- Knights, J., Vidanapathirana, K., Ramezani, M., Sridharan, S., Fookes, C. & Moghadam, P. (2023). Wild-Places: A Large-Scale Dataset for Lidar Place Recognition in Unstructured Natural Environments. Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA), 11322–11328. https://eprints.qut.edu.au/242816
- Fookes, C., Park, C., Moghadam, P., Williams, J., Kim, S. & Sridharan, S. (2022). Elasticity Meets Continuous-Time: Map-Centric Dense 3D LiDAR SLAM. IEEE Transactions on Robotics, 38(2), 978–997. https://eprints.qut.edu.au/232911
- Miller, D., Moghadam, P., Cox, M., Wildie, M. & Jurdak, R. (2022). What's in the Black Box? The False Negative Mechanisms Inside Object Detectors. IEEE Robotics and Automation Letters, 7(3), 8510–8517. https://eprints.qut.edu.au/232511
- Knights, J., Moghadam, P., Ramezani, M., Sridharan, S. & Fookes, C. (2022). InCloud: Incremental Learning for Point Cloud Place Recognition. Proceedings of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 8559–8566. https://eprints.qut.edu.au/237778
- Vidanapathirana, K., Ramezani, M., Moghadam, P., Sridharan, S. & Fookes, C. (2022). LoGG3D-Net: Locally Guided Global Descriptor Learning for 3D Place Recognition. Proceedings of the 39th IEEE International Conference on Robotics and Automation (ICRA 2022), 2215–2221. https://eprints.qut.edu.au/234466
- Stewart, I., Moghadam, P., Borg, D., Kung, T., Sikka, P. & Minett, G. (2020). Thermal infrared imaging can differentiate skin temperature changes associated with intense single leg exercise, but not with delayed onset of muscle soreness. Journal of Sports Science and Medicine, 19(3), 469–477. https://eprints.qut.edu.au/200728
QUT ePrints
For more publications by Peyman, explore their research in QUT ePrints (our digital repository).
Filter publications:
A complete list of publications is available at: https://www.qut.edu.au/about/our-people/academic-profiles/peyman.moghadam
Supervision
Current supervisions
- Lifelong Collaborative Learning
PhD, External Supervisor
Other supervisors: Emeritus Professor Sridha Sridharan, Professor Clinton Fookes, Dr Tharindu Fernando Warnakulasuriya - Self-Supervised Learning for 3D Multimodal Perception
PhD, External Supervisor
Other supervisors: Professor Clinton Fookes, Emeritus Professor Sridha Sridharan, Dr Tharindu Fernando Warnakulasuriya - Self-Supervised Neural Fields For Hyperspectral Learning
PhD, External Supervisor
Other supervisors: Dr Kien Nguyen Thanh, Emeritus Professor Sridha Sridharan, Professor Clinton Fookes - Deep Spatial-Spectral Representation Learning for Hyperspectral Data
PhD, External Supervisor
Other supervisors: Emeritus Professor Sridha Sridharan, Professor Clinton Fookes, Dr Tharindu Fernando Warnakulasuriya, Dr Maryam Haghighat
Completed supervisions (Doctorate)
The supervisions listed above are only a selection.