2026 Alun Preece: 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	41	8877	8626	538	531	302	6768

Overview

Alun Preece is affiliated with Cardiff University in the United Kingdom and has contributed extensively to the field of computer science, with a particular focus on artificial intelligence and its applications in social media and communications.

The primary areas of study for Alun Preece include:

Artificial Intelligence
Signal Processing
Sociology and Political Science
Computer Networks and Communications
Communication

Preece's research topics show a specialized interest in the intersection of AI and social behavior, covering themes such as:

Explainable Artificial Intelligence (XAI)
Topic Modeling
Social Media and Politics
Misinformation and Its Impacts
Time Series Analysis and Forecasting
Sentiment Analysis and Opinion Mining
Advanced Text Analysis Techniques

The scientist has published numerous papers in a variety of academic venues, including:

arXiv (Cornell University)
Online Social Networks and Media
Future Generation Computer Systems
Concurrency and Computation Practice and Experience
Patterns

Notable recent papers include:

Rapid Trust Calibration through Interpretable and Uncertainty-Aware AI (2020, Patterns)
Negativity spreads faster: A large-scale multilingual twitter analysis on the role of sentiment in political communication (2023, Online Social Networks and Media)
Real-Time Text Classification of User-Generated Content on Social Media: Systematic Review (2021, IEEE Transactions on Computational Social Systems)
DeepProbCEP: A neuro-symbolic approach for complex event processing in adversarial settings (2022, Expert Systems with Applications)
Efficient orchestration of Node-RED IoT workflows using a Vector Symbolic Architecture (2020, Future Generation Computer Systems)

Frequent collaborators in research have included:

Federico Cerutti
Mani Srivastava
Marc Roig Vilamala
Lance Kaplan
José Camacho-Collados

Best Publications

Interpretability of deep learning models: A survey of results

Supriyo Chakraborty;Richard Tomsett;Ramya Raghavendra;Daniel Harborne

461
Citations
Agent-based formation of virtual organisations

Timothy J. Norman;Alun Preece;Stuart Chalmers;Nicholas R. Jennings

349
Citations
The KRAFT architecture for knowledge fusion and transformation

A. Preece;K. Hui;A. Gray;P. Marti

288
Citations
AAMAS '05: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems

Jigar Patel;W. T. Luke Teacy;Nicholas R. Jennings;Michael Luck

221
Citations
Foundation and application of knowledge base verification

Alun D. Preece;Rajjan Shinghal

203
Citations
Agent-based virtual organisations for the Grid

Jigar Patel;W. T. Luke Teacy;Nicholas R. Jennings;Michael Luck

198
Citations
Asking ‘Why’ in AI: Explainability of intelligent systems – perspectives and challenges

Alun David Preece

168
Citations
Better knowledge management through knowledge engineering

A. Preece;A. Flett;D. Sleeman;D. Curry

165
Citations
Rapid Trust Calibration through Interpretable and Uncertainty-Aware AI.

Richard Tomsett;Alun D. Preece;Dave Braines;Federico Cerutti;Federico Cerutti

142
Citations
Towards a methodology for evaluating expert systems

Alun D. Preece

131
Citations
KRAFT: knowledge fusion from distributed databases and knowledge bases

P.M.D. Gray;A. Preece;N.J. Fiddian;W.A. Gray

125
Citations
An Ontology-Centric Approach to Sensor-Mission Assignment

Mario Gomez;Alun Preece;Matthew P. Johnson;Geeth Mel

123
Citations
Interpretable to whom? A role-based model for analyzing interpretable machine learning systems

Richard Tomsett;David Braines;Daniel Harborne;Alun David Preece

121
Citations
Principles and practice in verifying rule-based systems

Alun D. Preece;Rajjan Shinghal;Aïda Batarekh

117
Citations
KRAFT: AN AGENT ARCHITECTURE FOR KNOWLEDGE FUSION

Alun David Preece;Kit Hui;William Alexander Gray;Philippe Marti

106
Citations
Sanity checks for saliency metrics

Richard Tomsett;Daniel Harborne;Supriyo Chakraborty;Prudhvi Gurram

99
Citations
Verifying expert systems: A logical framework and a practical tool

Alun D. Preece;Rajjan Shinghal;Aïda Batarekh

98
Citations
The role of idioms in sentiment analysis

Lowri Williams;Christian Bannister;Michael Arribas-Ayllon;Alun Preece

97
Citations
CONOISE: Agent-based formation of virtual organisations

Timothy J. Norman;Alun D. Preece;Stuart W. Chalmers;Nicholas R. Jennings

91
Citations
Evaluating Verification and Validation Methods in Knowledge Engineering

Alun Preece

90
Citations
Stakeholders in explainable AI

Alun Preece;Daniel Harborne;David Braines;Richard Tomsett

66
Citations

Frequent Co-Authors

Timothy J. Norman University of Southampton

Ian Taylor University of Notre Dame

Michael Luck University of Sussex

Mani Srivastava University of California, Los Angeles

Lance Kaplan United States Army Research Laboratory

Nicholas R. Jennings Loughborough University

Thomas F. La Porta Pennsylvania State University

Amotz Bar-Noy City University of New York

Paolo Missier Newcastle University

Andrew J. Coates University College London

External Links

Personal website of Alun Preece Google Scholar page

If you think any of the details on this page are incorrect, let us know.

Related Online Degrees & Career Pathways

Choosing the right degree is vital for your success in computer science. Flexible study options, such as online associate degrees, are a great way to start a tech career quickly and affordably. These programs help you build a foundation and prepare for entry-level roles or continued study.

If you are eager to accelerate your education, explore the shortest master degree programs available online. These courses allow you to earn an advanced credential and boost your career prospects in less time.

When considering graduate programs, look for the most useful graduate degrees that match current industry demands. Specialized master’s programs in data science, artificial intelligence, cybersecurity, and software engineering are highly sought after by employers.

Cost is another key factor. Many students seek programs among the most affordable online colleges to reduce tuition expenses. Affordable options make it possible to advance your education without significant financial stress.