2026 Stephen Muggleton: 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	57	3758	3653	226	224	252	17916

Research.com Recognitions

2010 - Fellow of the Royal Academy of Engineering (UK)
2002 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to the theory and practice of inductive logic programming, especially applied to the discovery of new biomolecular theories from observational data.

Overview

Stephen Muggleton is affiliated with Imperial College London in the United Kingdom. Their research spans multiple disciplines, primarily within computer science and biochemistry, genetics, and molecular biology.

The main fields of study in Stephen Muggleton's work include:

Computer Science
Biochemistry, Genetics and Molecular Biology

The scientist's research covers detailed subfields such as:

Artificial Intelligence
Molecular Biology
Computational Theory and Mathematics
Information Systems
Biophysics

Main topics addressed in their work include:

Logic, Reasoning, and Knowledge
Explainable Artificial Intelligence (XAI)
Topic Modeling
Gene Regulatory Network Analysis
Computability, Logic, AI Algorithms
AI-based Problem Solving and Planning
Machine Learning and Algorithms

Stephen Muggleton has published extensively, with frequent appearances in several venues. The top publication venues are:

arXiv (Cornell University)
Machine Learning
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
Proceedings of the AAAI Conference on Artificial Intelligence

Recent notable papers include:

Inductive logic programming at 30, 2021, published in Machine Learning
Beneficial and harmful explanatory machine learning, 2021, published in Machine Learning
Introduction to 'Cognitive artificial intelligence', 2023, published in Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
Explanatory machine learning for sequential human teaching, 2023, published in Machine Learning
Top program construction and reduction for polynomial time Meta-Interpretive learning, 2021, published in Machine Learning

Frequent co-authors collaborating with Stephen Muggleton include:

Lun Ai
Geoff Baldwin
Shi-Shun Liang
Ute Schmid
Stassa Patsantzis

Stephen Muggleton has received professional recognition, including the following awards:

Fellow of the Royal Academy of Engineering (UK), awarded in 2010
Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), awarded in 2002, for contributions to the theory and practice of inductive logic programming, especially in biomolecular theory discovery from observational data

Best Publications

Inductive Logic Programming : Theory and Methods

Stephen Muggleton;Luc de Raedt

2267
Citations
Inverse entailment and PROGOL

Stephen Muggleton

2183
Citations
Efficient Induction of Logic Programs

S. Muggleton;C. Feng

1218
Citations
Functional genomic hypothesis generation and experimentation by a robot scientist

Ross D. King;Kenneth E. Whelan;Ffion M. Jones;Philip G. K. Reiser

847
Citations
Machine invention of first order predicates by inverting resolution

Stephen Muggleton;Wray L. Buntine

775
Citations
Theories for mutagenicity: a study in first-order and feature-based induction

Ashwin Srinivasan;S. H. Muggleton;M. J. E. Sternberg;R. D. King

454
Citations
Drug design by machine learning: the use of inductive logic programming to model the structure-activity relationships of trimethoprim analogues binding to dihydrofolate reductase.

Ross D. King;Stephen Muggleton;Richard A. Lewis;Michael J. E. Sternberg

387
Citations
Protein secondary structure prediction using logic-based machine learning

S. Muggleton;R.D. King;M.J.E. Sternberg

386
Citations
Structure-activity relationships derived by machine learning: the use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming.

Ross D. King;Stephen H. Muggleton;Ashwin Srinivasan;Michael J. E. Sternberg

354
Citations
Stochastic Logic Programs

Unknown

338
Citations
Learning from Positive Data

Stephen Muggleton

337
Citations
Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited

Stephen H. Muggleton;Dianhuan Lin;Alireza Tamaddoni-Nezhad

244
Citations
Applications of inductive logic programming

Ivan Bratko;Stephen Muggleton

233
Citations
Duce, an oracle-based approach to constructive induction

Stephen Muggleton

211
Citations
Inductive programming meets the real world

Sumit Gulwani;José Hernández-Orallo;Emanuel Kitzelmann;Stephen H. Muggleton

197
Citations
Carcinogenesis Predictions Using ILP

Ashwin Srinivasan;Ross D. King;Stephen Muggleton;Michael J. E. Sternberg

188
Citations
ILP turns 20

Stephen Muggleton;Luc Raedt;David Poole;Ivan Bratko

181
Citations
Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL

Paul Finn;Stephen Muggleton;David Page;Ashwin Srinivasan

176
Citations
Meta-interpretive learning: application to grammatical inference

Stephen H. Muggleton;Dianhuan Lin;Niels Pahlavi;Alireza Tamaddoni-Nezhad

166
Citations
The predictive toxicology evaluation challenge

A. Srinivasan;R. D. King;S. H. Muggleton;M. J. E. Sternberg

159
Citations
Learning Stochastic Logic Programs

Stephen Muggleton

157
Citations
Inductive logic programming

Stephen Muggleton

152
Citations

Frequent Co-Authors

Michael J.E. Sternberg Imperial College London

Ross D. King University of Manchester

Luc De Raedt KU Leuven

Lise Getoor University of California, Santa Cruz

Thomas G. Dietterich Oregon State University

Antonis C. Kakas University of Cyprus

Ivan Bratko University of Ljubljana

David L. Page MIT

Brendan W. Wren London School of Hygiene & Tropical Medicine

Stephen G. Oliver University of Cambridge

External Links

Wikipedia of Stephen Muggleton Personal website of Stephen Muggleton Google Scholar page

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