Sotabase

Career

· Co-Founder And Chief Scientist, Trent AI2025–
· The DeepMind Professor Of Machine Learning, University of Cambridge2019–
· Director, IPC Machine Learning, Amazon2018–2019
· Director, Core Machine Learning, Amazon2016–2018
· Professor Of Machine Learning, The University of Sheffield2010–
· Senior Research Fellow, The University of Manchester2007–2010
· Senior Lecturer, University of Sheffield2005–2006
· Lecturer, University of Sheffield2001–2005
· Postdoctoral Researcher, Microsoft Research2000–2001
· Doctor of Philosophy (Ph.D.), Computer Science, University of Cambridge1998–2000
· Field Engineer, Schlumberger Wire Line1995–1997
· Bachelor’s Degree, Mechanical Engineering, 1st Class Honours, University of Southampton1991–1995

Publications (284)

Dataset Shift in Machine Learning
2009
2,141
cited
Gaussian Processes for Big Data
Conference on Uncertainty in Artificial Intelligence · 2013
1,310
cited
Deep Gaussian Processes
International Conference on Artificial Intelligence and Statistics · 2012
1,275
cited
Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models
Journal of machine learning research · 2005
1,121
cited
Kernels for Vector-Valued Functions: a Review
Found. Trends Mach. Learn. · 2011
1,010
cited
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
Neural Information Processing Systems · 2003
881
cited
Variational Information Distillation for Knowledge Transfer
Computer Vision and Pattern Recognition · 2019
714
cited
Fast Sparse Gaussian Process Methods: The Informative Vector Machine
Neural Information Processing Systems · 2002
613
cited
WiFi-SLAM Using Gaussian Process Latent Variable Models
International Joint Conference on Artificial Intelligence · 2007
577
cited
Fast Forward Selection to Speed Up Sparse Gaussian Process Regression
International Conference on Artificial Intelligence and Statistics · 2003
519
cited
Bayesian Gaussian Process Latent Variable Model
International Conference on Artificial Intelligence and Statistics · 2010
513
cited
Challenges in Deploying Machine Learning: A Survey of Case Studies
ACM Computing Surveys · 2020
508
cited
Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling
Proceedings of the Royal Society A · 2017
419
cited
Learning to learn with the informative vector machine
International Conference on Machine Learning · 2004
393
cited
Batch Bayesian Optimization via Local Penalization
International Conference on Artificial Intelligence and Statistics · 2015
387
cited
Computationally Efficient Convolved Multiple Output Gaussian Processes
Journal of machine learning research · 2011
336
cited
Gaussian Processes
International Encyclopedia of Statistical Science · 2020
314
cited
When Training and Test Sets Are Different: Characterizing Learning Transfer
2009
300
cited
Local distance preservation in the GP-LVM through back constraints
International Conference on Machine Learning · 2006
276
cited
Non-linear matrix factorization with Gaussian processes
International Conference on Machine Learning · 2009
251
cited
Sotabase