I am a final year Ph.D. student at Imperial College London, advised by Prof. Andrew Davison. Previously, I completed my undergraduate and Masters in Physics at the University of Oxford.

My research interests lie in building efficient real-time scene understanding systems for robotics. Towards this goal, my research focuses on two directions: 1) graphical representations and Gaussian Belief Propagation as a distributed inference algorithm for fast computer vision, and 2) training neural scene representations via continual learning for real-time robotics.


March 2020
Theseus was accepted to NeurIPS 2022!
April 2022
iSDF accepted to RSS 2022!
August 2021
I'll be interning at Facebook AI Research with Mustafa Mukadam this autumn.
July 2021
iMAP accepted to ICCV 2021!
July 2021


Theseus: A Library for Differentiable Nonlinear Optimization
NeurIPS 2022
Luis Pineda, Taosha Fan, Maurizio Monge, Shobha Venkataraman, Paloma Sodhi,
Ricky Chen, Joseph Ortiz, Daniel DeTone, Austin Wang, Stuart Anderson,
Jing Dong, Brandon Amos, Mustafa Mukadam
iSDF: Real-Time Neural Signed Distance Fields for Robot Perception
RSS 2022
Joseph Ortiz, Alexander Clegg, Jing Dong, Edgar Sucar, David Novotny,
Michael Zollhoefer, Mustafa Mukadam
A Robot Web for Distributed Many-Device Localisation
arXiv 2022
Riku Murai, Joseph Ortiz, Sajad Saeedi, Paul Kelly, Andrew J. Davison
Incremental Abstraction in Distributed Probabilistic SLAM Graphs
ICRA 2022
Joseph Ortiz, Talfan Evans, Edgar Sucar, Andrew J. Davison
iMAP: Implicit Mapping and Positioning in Real-Time
ICCV 2021
Edgar Sucar, Shikun Liu, Joseph Ortiz, Andrew J. Davison
A visual introduction to Gaussian Belief Propagation
Self published / arXiv 2021
Joseph Ortiz, Talfan Evans, Andrew J. Davison
Bundle Adjustment on a Graph Processor
CVPR 2020
Joseph Ortiz, Mark Pupilli, Stefan Leutenegger, Andrew J. Davison
FutureMapping 2: Gaussian Belief Propagation for Spatial AI
arXiv 2019
Andrew J. Davison, Joseph Ortiz