2026 David Barber: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	38	10008	9723	625	617	155	9527

Overview

David Barber is affiliated with University College London in the United Kingdom. Their research spans computer science with a primary focus on artificial intelligence and machine learning applications in biomedical contexts.

The main fields of study of David Barber include:

Computer Science

Their subfields of research cover:

Artificial Intelligence
Pulmonary and Respiratory Medicine
Computer Vision and Pattern Recognition
Radiology, Nuclear Medicine and Imaging
Signal Processing

David Barber's work addresses multiple topics related to AI and biomedical imaging, including:

Adversarial Robustness in Machine Learning
Generative Adversarial Networks and Image Synthesis
Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Anomaly Detection Techniques and Applications
Domain Adaptation and Few-Shot Learning
Topic Modeling
Natural Language Processing Techniques

Recent papers authored or co-authored by David Barber include:

"Towards algorithm auditing: managing legal, ethical and technological risks of AI, ML and associated algorithms" (2024), published in Royal Society Open Science
"Mortality surrogates in combined pulmonary fibrosis and emphysema" (2023), published in European Respiratory Journal
"A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study" (2023), published in Heliyon
"CenTime: Event-conditional modelling of censoring in survival analysis" (2023), published in Medical Image Analysis
"Towards AI Standards: Thought-Leadership in Ai Legal, Ethical and Safety Specifications Through Experimentation" (2021), published in SSRN Electronic Journal

The frequent collaborators in their research include:

Ming-Tian Zhang
Daniel C. Alexander
Joseph Jacob
An Zhao
Emine Yılmaz

David Barber has published extensively in venues such as:

arXiv (Cornell University)
Royal Society Open Science
European Respiratory Journal
Heliyon
Medical Image Analysis

Best Publications

Bayesian Reasoning and Machine Learning

David Barber

2357
Citations
Bayesian classification with Gaussian processes

C.K.I. Williams;D. Barber

1079
Citations
The IM algorithm: a variational approach to Information Maximization

David Barber;Felix Agakov

349
Citations
Optimal spike-timing-dependent plasticity for precise action potential firing in supervised learning

Jean-Pascal Pfister;Taro Toyoizumi;David Barber;Wulfram Gerstner

320
Citations
Thinking Fast and Slow with Deep Learning and Tree Search

Thomas Anthony;Zheng Tian;David Barber

245
Citations
Ensemble learning in Bayesian neural networks

D. Barber;Christopher M. Bishop

237
Citations
A Scalable Laplace Approximation for Neural Networks

Hippolyt Ritter;Aleksandar Botev;David Barber

203
Citations
Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting

Hippolyt Ritter;Aleksandar Botev;David Barber

188
Citations
A generative model for music transcription

A.T. Cemgil;H.J. Kappen;D. Barber

169
Citations
Bayesian Time Series Models

David Barber;A. Taylan Cemgil;Silvia Chiappa

141
Citations
Practical Gauss-Newton Optimisation for Deep Learning

Aleksandar Botev;Hippolyt Ritter;David Barber

135
Citations
Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo

David Barber;Christopher K. I. Williams

113
Citations
Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems

David Barber

111
Citations
Nesterov's accelerated gradient and momentum as approximations to regularised update descent

Aleksandar Botev;Guy Lever;David Barber

111
Citations
Ensemble Learning for Multi-Layer Networks

David Barber;Christopher M. Bishop

111
Citations
Switching Linear Dynamical Systems for Noise Robust Speech Recognition

B.. Mesot;D.. Barber

89
Citations
Graphical Models for Time-Series

David Barber;A Taylan Cemgil

88
Citations
Towards Algorithm Auditing: A Survey on Managing Legal, Ethical and Technological Risks of AI, ML and Associated Algorithms

Adriano Koshiyama;Emre Kazim;Philip Treleaven;Pete Rai

88
Citations
On the Computational Complexity of Stochastic Controller Optimization in POMDPs

Nikos Vlassis;Michael L. Littman;David Barber

81
Citations
Gaussian Processes for Bayesian Estimation in Ordinary Differential Equations

David Barber;Yali Wang

80
Citations
Practical lossless compression with latent variables using bits back coding

James Townsend;Thomas Bird;David Barber

76
Citations
Modular Networks: Learning to Decompose Neural Computation

Louis Kirsch;Julius Kunze;David Barber

41
Citations

Frequent Co-Authors

David Saad Aston University

James T. Townsend Indiana University

Christopher M. Bishop Microsoft (United States)

Zhen He Washington University in St. Louis

Nikos Vlassis Adobe Systems (United States)

Tom Heskes Radboud University

Michael L. Littman Brown University

Hilbert J. Kappen Radboud University

Wulfram Gerstner École Polytechnique Fédérale de Lausanne

Tomas Chamorro-Premuzic University College London

External Links

Personal website of David Barber Google Scholar page

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