Biography
Gadd is a Postdoctoral Research Assistant (PDRA) at the University of Oxford and a Junior Research Fellow at Kellogg College. He works with Professor Paul Newman in the Mobile Robotics Group (MRG), part of the Oxford Robotics Institute (ORI). Gadd originally joined MRG as a student reading for a DPhil in Engineering Science at Keble College. Before arriving in the United Kingdom, he was an undergraduate student at the University of Cape Town, South Africa, where he studied Mechatronics Engineering.
Research Interests
- Robotics,
- Autonomous Vehicles,
- Computer Vision,
- Machine Learning
Research Groups
Current Projects
Sense Assess eXplain (SAX) - acceptably auditable action from autonomous vehicles in formidable environments is only going to be possible with robust sensors and sensing which are nevertheless introspective where unavoidably fallible
Related Academics
Recent Publications
Off the radar: uncertainty-aware radar place recognition with introspective querying and map maintenance
Yuan J, Newman P & Gadd M (2023), 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1350-1357
BibTeX
@inproceedings{offtheradarunce-2023/12,
title={Off the radar: uncertainty-aware radar place recognition with introspective querying and map maintenance},
author={Yuan J, Newman P & Gadd M},
booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023)},
pages={1350-1357},
year = "2023"
}
Visual servoing on wheels: robust robot orientation estimation in remote viewpoint control
Robinson L, De Martini D, Gadd M & Newman P (2023), 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 6364-6370
BibTeX
@inproceedings{visualservoingo-2023/12,
title={Visual servoing on wheels: robust robot orientation estimation in remote viewpoint control},
author={Robinson L, De Martini D, Gadd M & Newman P},
booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023)},
pages={6364-6370},
year = "2023"
}
Visual DNA: representing and comparing images using distributions of neuron activations
Ramtoula B, Gadd M, Newman P & De Martini D (2023), 11113-11123
BibTeX
@inproceedings{visualdnarepres-2023/8,
title={Visual DNA: representing and comparing images using distributions of neuron activations},
author={Ramtoula B, Gadd M, Newman P & De Martini D},
booktitle={IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR 2023)},
pages={11113-11123},
year = "2023"
}
Fast-MbyM: leveraging translational invariance of the fourier transform for efficient and accurate radar odometry
Weston R, Gadd M, De Martini D, Newman P & Posner H (2022), Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2022), 2186-2192
BibTeX
@inproceedings{fastmbymleverag-2022/7,
title={Fast-MbyM: leveraging translational invariance of the fourier transform for efficient and accurate radar odometry},
author={Weston R, Gadd M, De Martini D, Newman P & Posner H},
booktitle={IEEE International Conference on Robotics and Automation (ICRA 2022)},
pages={2186-2192},
year = "2022"
}
Depth-SIMS: semi-parametric image and depth synthesis
Musat V, De Martini D, Gadd M & Newman P (2022), 2022 International Conference on Robotics and Automation (ICRA), 2388-2394
BibTeX
@inproceedings{depthsimssemipa-2022/7,
title={Depth-SIMS: semi-parametric image and depth synthesis},
author={Musat V, De Martini D, Gadd M & Newman P},
booktitle={ International Conference on Robotics and Automation (ICRA 2022)},
pages={2388-2394},
year = "2022"
}
What goes around: leveraging a constant-curvature motion constraint in radar odometry
Aldera R, Gadd M, De Martini D & Newman P (2022), IEEE Robotics and Automation Letters, 7(3), 7865-7872
BibTeX
@article{whatgoesaroundl-2022/6,
title={What goes around: leveraging a constant-curvature motion constraint in radar odometry},
author={Aldera R, Gadd M, De Martini D & Newman P},
journal={IEEE Robotics and Automation Letters},
volume={7},
pages={7865-7872},
publisher={IEEE},
year = "2022"
}
Contrastive learning for unsupervised radar place recognition
Gadd M, De Martini D & Newman P (2022), 2021 20th International Conference on Advanced Robotics (ICAR), 344-349
BibTeX
@inproceedings{contrastivelear-2022/1,
title={Contrastive learning for unsupervised radar place recognition},
author={Gadd M, De Martini D & Newman P},
booktitle={20th International Conference on Advanced Robotics (ICAR 2021)},
pages={344-349},
year = "2022"
}
The Oxford Road Boundaries Dataset
Suleymanov T, Gadd M, De Martini D & Newman P (2022)
BibTeX
@inproceedings{theoxfordroadbo-2022/1,
title={The Oxford Road Boundaries Dataset},
author={Suleymanov T, Gadd M, De Martini D & Newman P},
booktitle={32nd IEEE Intelligent Vehicles Symposium (IV21) -- Workshop on 3D-Deep Learning for Automated Driving (3D-DLAD)},
year = "2022"
}
BoxGraph: semantic place recognition and pose estimation from 3D LiDAR
Pramatarov G, De Martini D, Gadd M & Newman P (2021), 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 7004-7011
BibTeX
@inproceedings{boxgraphsemanti-2021/12,
title={BoxGraph: semantic place recognition and pose estimation from 3D LiDAR},
author={Pramatarov G, De Martini D, Gadd M & Newman P},
booktitle={2022 IEEE/RSJ International Conference on Intelligent Robots and Systems},
pages={7004-7011},
year = "2021"
}
Fool me once: robust selective segmentation via out-of-distribution detection with contrastive learning
Williams D, Gadd M, De Martini D & Newman P (2021), 2021 IEEE International Conference on Robotics and Automation (ICRA), 9536-9542
BibTeX
@inproceedings{foolmeoncerobus-2021/10,
title={Fool me once: robust selective segmentation via out-of-distribution detection with contrastive learning},
author={Williams D, Gadd M, De Martini D & Newman P},
booktitle={ICRA 2021},
pages={9536-9542},
year = "2021"
}
Google Scholar
Awards and Prizes
2013 FirstRand Laurie Dippenaar Scholarship
