2026 Adam Prügel-Bennett: 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	34	12138	11786	772	759	150	5199

Overview

Adam Prügel-Bennett is affiliated with the University of Southampton in the United Kingdom. Their research spans predominantly within Computer Science, with a focus on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering, Ocean Engineering, and Oceanography.

The scientist has published extensively across various venues. Frequent publication venues include:

arXiv (Cornell University)
ePrints Soton (University of Southampton)
Journal of Field Robotics
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Robotics and Automation Letters

Notable recent papers illustrate a concentration on advanced machine learning approaches applied to imagery and robotics, particularly in underwater environments. Selected papers include:

"FMix: Enhancing Mixed Sample Data Augmentation" (2020) published in arXiv (Cornell University)
"Learning features from georeferenced seafloor imagery with location guided autoencoders" (2020) published in Journal of Field Robotics
"Guiding Labelling Effort for Efficient Learning With Georeferenced Images" (2022) published in IEEE Transactions on Pattern Analysis and Machine Intelligence
"Leveraging Metadata in Representation Learning With Georeferenced Seafloor Imagery" (2021) published in IEEE Robotics and Automation Letters
"GeoCLR: Georeference Contrastive Learning for Efficient Seafloor Image Interpretation" (2022) published in Field Robotics

The main topics underpinning their work encompass a range of areas from machine learning methods to underwater technology and image analysis. These topics include:

Domain Adaptation and Few-Shot Learning
Advanced Neural Network Applications
Industrial Vision Systems and Defect Detection
Generative Adversarial Networks and Image Synthesis
Underwater Vehicles and Communication Systems
Underwater Acoustics Research
Advanced Image and Video Retrieval Techniques

The scientist collaborates frequently with several co-authors. Most common collaborators are:

Xiaohao Cai
Jonathon Hare
Halil Ibrahim Aysel
Ruixiao Zhang
Takaki Yamada

Best Publications

SVM Parameter Optimization using Grid Search and Genetic Algorithm to Improve Classification Performance

Iwan Syarif;Adam Prugel-Bennett;Gary Wills

502
Citations
Analysis of genetic algorithms using statistical mechanics.

Adam Prügel-Bennett;Jonathan L. Shapiro

301
Citations
Novel centroid selection approaches for KMeans-clustering based recommender systems

Sobia Zahra;Mustansar Ali Ghazanfar;Asra Khalid;Muhammad Awais Azam

258
Citations
Unsupervised Clustering Approach for Network Anomaly Detection

Iwan Syarif;Adam Prugel-Bennett;Gary B. Wills

254
Citations
Automatic gait recognition using area-based metrics

Jeff P. Foster;Mark S. Nixon;Adam Prügel-Bennett

228
Citations
A Scalable, Accurate Hybrid Recommender System

Mustansar Ali Ghazanfar;Adam Prugel-Bennett

204
Citations
Learning to count objects in natural images for visual question answering

Yan Zhang;Jonathon S. Hare;Adam Prügel-Bennett

192
Citations
Analysis of synfire chains

M Herrmann;J A Hertz;A Prügel-Bennett

168
Citations
Genetic drift in genetic algorithm selection schemes

A. Rogers;A. Prugel-Bennett

166
Citations
Application of bagging, boosting and stacking to intrusion detection

Iwan Syarif;Ed Zaluska;Adam Prugel-Bennett;Gary Wills

165
Citations
Leveraging clustering approaches to solve the gray-sheep users problem in recommender systems

Mustansar Ali Ghazanfar;Adam Prügel-Bennett

156
Citations
The dynamics of a genetic algorithm for simple random Ising systems

Adam Prügel-Bennett;Jonathan L. Shapiro

138
Citations
FMix: Enhancing Mixed Sample Data Augmentation

Ethan Harris;Antonia Marcu;Matthew Painter;Mahesan Niranjan

121
Citations
Benefits of a Population: Five Mechanisms That Advantage Population-Based Algorithms

Adam Prügel-Bennett

109
Citations
Modelling the Dynamics of a Steady State Genetic Algorithm

Alex Rogers;Adam Prügel-Bennett

100
Citations
An Improved Switching Hybrid Recommender System Using Naive Bayes Classifier and Collaborative Filtering

Mustansar Ali Ghazanfar;Adam Prugel-Bennett

97
Citations
Modelling Evolving Populations

Adam Prügel-Bennett

96
Citations
When a genetic algorithm outperforms hill-climbing

Adam Prügel-Bennett

88
Citations
Training HMM structure with genetic algorithm for biological sequence analysis

Kyoung-Jae Won;Adam Prügel-Bennett;Anders Krogh

87
Citations
On the Landscape of Combinatorial Optimization Problems

Mohammad-H. Tayarani-N.;Adam Prugel-Bennett

83
Citations
A Statistical Mechanical Formulation of the Dynamics of Genetic Algorithms

Jonathan Shapiro;Adam Prügel-Bennett;Magnus Rattray

79
Citations

Frequent Co-Authors

Mark S. Nixon University of Southampton

Alex Rogers University of Oxford

Anders Krogh University of Copenhagen

Gary Wills University of Southampton

mc schraefel University of Southampton

Magnus Rattray University of Manchester

Nicholas R. Jennings Loughborough University

Nigel Shadbolt University of Oxford

Guang-Zhong Yang Shanghai Jiao Tong University

Stefan B. Williams University of Sydney

External Links

Personal website of Adam Prügel-Bennett

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