Alex Kendall
Wayve Co-founder and CEO
I founded Wayve in 2017 to bring embodied AI to the physical world. We build the foundation models that let vehicles drive themselves — deploying with consumer cars and robotaxis globally. If you're excited by our mission, we're hiring for roles across our global team.
I grew up in the South Island of New Zealand spending most of my time on adventures in the mountains or building technology.
Before Wayve, I was at Cambridge and worked on some of the first end-to-end deep learning approaches to computer vision and robotics — a selection of my publications are below.
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Selected Media
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My ride with Bill Gates around London GatesNotes, 2023 -
The Tokyo Challenge, with Masa Wayve and SoftBank, 2025 -
60 Minutes: Robotaxis coming to London CBS News, 2026 -
AI Is Reshaping Self-Driving Cars Bloomberg, 2026
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Awards and Prizes
- Officer of the Order of the British Empire (OBE), for services to Artificial Intelligence. 2025 New Year Honours.
- MIT Technology Review Innovators Under 35, for contributions to AI and technology entrepreneurship. 2025.
- Forbes 30 Under 30, for contributions to technology entrepreneurship. 2020.
- ELLIS European PhD Prize and BMVA Prize, for my PhD research. 2019 and 2018.
- PITCH Champions at WebSummit. 2018.
- Research Fellowship at Trinity College, Cambridge University. 2017.
03
Publications
Also on Google Scholar.
- LingoQA: Video question answering for autonomous driving. arXiv, 2023. Ana-Maria Marcu, Long Chen, Jan Hünermann, Alice Karnsund, Benoit Hanotte, Prajwal Chidananda, Saurabh Nair, Vijay Badrinarayanan, Alex Kendall, Jamie Shotton, Elahe Arani, Oleg Sinavski
- GAIA-1: A generative world model for autonomous driving. arXiv, 2023. Anthony Hu, Lloyd Russell, Hudson Yeo, Zak Murez, George Fedoseev, Alex Kendall, Jamie Shotton, Gianluca Corrado
- Model-based imitation learning for urban driving. NeurIPS, 2022. Anthony Hu, Gianluca Corrado, Nicolas Griffiths, Zak Murez, Corina Gurau, Hudson Yeo, Alex Kendall, Roberto Cipolla, Jamie Shotton
- Geometry and Uncertainty in Deep Learning for Computer Vision. PhD Thesis, University of Cambridge, 2017. Alex Kendall
- FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Cameras. ICCV (Oral), 2021. Anthony Hu, Zak Murez, Nikhil Mohan, Sofía Dudas, Jeffrey Hawke, Vijay Badrinarayanan, Roberto Cipolla, Alex Kendall
- Probabilistic Future Prediction for Video Scene Understanding. ECCV, 2020. Anthony Hu, Fergal Cotter, Nikhil Mohan, Corina Gurau, Alex Kendall
- Urban Driving with Conditional Imitation Learning. ICRA, 2020. Jeffrey Hawke, Richard Shen, Corina Gurau, Siddharth Sharma, Daniele Reda, Nikolay Nikolov, Przemyslaw Mazur, Sean Micklethwaite, Nicolas Griffiths, Amar Shah, Alex Kendall
- Orthographic Feature Transform for Monocular 3D Object Detection. BMVC (Oral, Best Paper Honourable Mention), 2019. Thomas Roddick, Alex Kendall, Roberto Cipolla
- Learning to Drive from Simulation without Real World Labels. ICRA, 2019. Alex Bewley, Jessica Rigley, Yuxuan Liu, Jeffrey Hawke, Richard Shen, Vinh-Dieu Lam, Alex Kendall
- Learning to Drive in a Day. ICRA, 2019. Alex Kendall, Jeffrey Hawke, David Janz, Przemyslaw Mazur, Daniele Reda, John-Mark Allen, Vinh-Dieu Lam, Alex Bewley, Amar Shah
- Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics. CVPR (Spotlight Oral), 2018. Alex Kendall, Yarin Gal, Roberto Cipolla
- Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning. IJCAI (Special Track — AI & Autonomy), 2017. Rowan McAllister, Yarin Gal, Alex Kendall, Mark van der Wilk, Amar Shah, Roberto Cipolla, Adrian Weller
- Concrete Dropout. NeurIPS, 2017. Yarin Gal, Jiri Hron, Alex Kendall
- Geometric loss functions for camera pose regression with deep learning. CVPR (Spotlight Oral), 2017. Alex Kendall, Roberto Cipolla
- What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? NeurIPS (Spotlight Oral), 2017. Alex Kendall, Yarin Gal
- Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding. BMVC, 2017. Alex Kendall, Vijay Badrinarayanan, Roberto Cipolla
- End-to-End Learning of Geometry and Context for Deep Stereo Regression. ICCV (Spotlight Oral), 2017. Alex Kendall, Hayk Martirosyan, Saumitro Dasgupta, Peter Henry, Ryan Kennedy, Abraham Bachrach, Adam Bry
- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation. PAMI, 2017. Vijay Badrinarayanan, Alex Kendall, Roberto Cipolla
- Modelling Uncertainty in Deep Learning for Camera Relocalization. ICRA, 2016. Alex Kendall, Roberto Cipolla
- PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization. ICCV, 2015. Alex Kendall, Matthew Grimes, Roberto Cipolla
- On-board object tracking control of a quadcopter with monocular vision. ICUAS, 2014. Alex Kendall, Nishaad Salvapantula, Karl Stol