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Matt Gadd

Dr

Matthew Gadd DPhil (Oxon), BSc

Postdoctoral Research Assistant

Junior Research Fellow

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

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

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BibTeX View PDF
@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

Altmetric score is
BibTeX View PDF
@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)

Altmetric score is
BibTeX View PDF
@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"
}

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

Altmetric score is
BibTeX View PDF
@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"
}

The hulk: design and development of a weather-proof vehicle for long-term autonomy in outdoor environments

Kyberd S, Attias J, Get P, Murcutt P, Prahacs C et al. (2021), International Conference on Field and Service Robotics (FSR), 16(2021), 101-114

Altmetric score is
BibTeX View PDF
@inproceedings{thehulkdesignan-2021/1,
  title={The hulk: design and development of a weather-proof vehicle for long-term autonomy in outdoor environments},
  author={Kyberd S, Attias J, Get P, Murcutt P, Prahacs C et al.},
  pages={101-114},
  year = "2021"
}

RSS-Net: weakly-supervised multi-class semantic segmentation with FMCW radar

Kaul P, De Martini D, Gadd M & Newman P (2021), Proceedings of the 2020 IEEE Intelligent Vehicles Symposium (IV2020)(2020), 431-436

Altmetric score is
BibTeX View PDF
@inproceedings{rssnetweaklysup-2021/1,
  title={RSS-Net: weakly-supervised multi-class semantic segmentation with FMCW radar},
  author={Kaul P, De Martini D, Gadd M & Newman P},
  booktitle={IEEE Intelligent Vehicles Symposium (IV)},
  pages={431-436},
  year = "2021"
}

Sense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenarios

Gadd M, De Martini D, Marchegiani M, Newman P & Kunze L (2021), Proceedings of the 2020 IEEE Intelligent Vehicles Symposium (IV), 150-155

Altmetric score is
BibTeX View PDF
@inproceedings{senseassessexpl-2021/1,
  title={Sense-Assess-eXplain (SAX): building trust in autonomous vehicles in challenging real-world driving scenarios},
  author={Gadd M, De Martini D, Marchegiani M, Newman P & Kunze L},
  booktitle={IEEE Intelligent Vehicles Symposium (IV), Workshop on Ensuring and Validating Safety for Automated Vehicles (EVSAV)},
  pages={150-155},
  year = "2021"
}

Look Here: Learning Geometrically Consistent Refinement of Inverse-Depth Images for 3D Reconstruction

Sǎftescu A, Gadd M & Newman P (2021), International Journal of Pattern Recognition and Artificial Intelligence

Altmetric score is
BibTeX View PDF
@article{lookherelearnin-2021/1,
  title={Look Here: Learning Geometrically Consistent Refinement of Inverse-Depth Images for 3D Reconstruction},
  author={Sǎftescu A, Gadd M & Newman P},
  journal={International Journal of Pattern Recognition and Artificial Intelligence},
  year = "2021"
}

Keep off the grass: permissible driving routes from radar with weak audio supervision

Williams D, De Martini D, Gadd M, Marchegiani M & Newman P (2020), Proceedings of the 2020 IEEE Intelligent Transportation Systems Conference (ITSC), 1-6

Altmetric score is
BibTeX View PDF
@inproceedings{keepoffthegrass-2020/12,
  title={Keep off the grass: permissible driving routes from radar with weak audio supervision},
  author={Williams D, De Martini D, Gadd M, Marchegiani M & Newman P},
  booktitle={IEEE Intelligent Transportation Systems Conference (ITSC)},
  pages={1-6},
  year = "2020"
}

On the road: route proposal from radar self-supervised by fuzzy LiDAR traversability

Broome M, Gadd M, De Martini D & Newman P (2020), AI, 1(4), 558-585

Altmetric score is
BibTeX View PDF
@article{ontheroadroutep-2020/12,
  title={On the road: route proposal from radar self-supervised by fuzzy LiDAR traversability},
  author={Broome M, Gadd M, De Martini D & Newman P},
  journal={AI},
  volume={1},
  pages={558-585},
  publisher={MDPI},
  year = "2020"
}
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Google Scholar

Awards and Prizes

2013 FirstRand Laurie Dippenaar Scholarship