2026 Jan Ramon: 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	32	13122	12734	337	327	235	4740

Overview

Jan Ramon is a researcher affiliated with the French Institute for Research in Computer Science and Automation (INRIA) in France. Their work spans multiple domains within computer science, with a strong focus on privacy-preserving technologies and cryptography.

Ramon's research portfolio includes contributions to several subfields, notably:

Artificial Intelligence
Computational Theory and Mathematics
Molecular Biology
Oncology
Statistics and Probability

Their main research topics consist of:

Privacy-Preserving Technologies in Data
Cryptography and Data Security
Internet Traffic Analysis and Secure E-voting
Complexity and Algorithms in Graphs
Algorithms and Data Compression
Semigroups and Automata Theory
DNA and Biological Computing

Jan Ramon has published extensively in leading scientific venues. Frequent publication outlets include:

arXiv (Cornell University)
Zenodo (CERN European Organization for Nuclear Research)
Machine Learning
Journal of Controlled Release
HAL (Le Centre pour la Communication Scientifique Directe)

Some recent papers authored or co-authored by Ramon are:

"An accurate, scalable and verifiable protocol for federated differentially private averaging," 2022, Machine Learning
"Naive Infinite Enumeration of Context-free Languages in Incremental Polynomial Time," 2020, Lirias (KU Leuven)
"Private Sampling with Identifiable Cheaters," 2023, Proceedings on Privacy Enhancing Technologies
"An Accurate, Scalable and Verifiable Protocol for Federated Differentially Private Averaging," 2020, arXiv (Cornell University)
"Immunogenic cell death as interplay between physical anticancer modalities and immunotherapy," 2025, Journal of Controlled Release

Ramon collaborates frequently with several other researchers, including:

César Sabater
Florian Hahn
Peter Andreas
Aurélien Bellet
Stefaan C. De Smedt

Their research encompasses both theoretical and applied aspects, engaging with complex algorithms and privacy protocols as well as interdisciplinary areas like molecular biology and oncology.

Best Publications

Top-Down Induction of Clustering Trees

Hendrik Blockeel;Luc De Raedt;Jan Ramon

588
Citations
Expressivity versus efficiency of graph kernels

Jan Ramon;Thomas Gaertner

321
Citations
Multi instance neural networks

Jan Ramon;Luc De Raedt

244
Citations
Improving the efficiency of inductive logic programming through the use of query packs

Hendrik Blockeel;Luc Dehaspe;Bart Demoen;Gerda Janssens

168
Citations
Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases

Kevin Stewart Williams;Elizabeth Bilsland;Andrew Charles Sparkes;Wayne Aubrey

166
Citations
Machine learning techniques to examine large patient databases.

Geert Meyfroidt;Fabian Güiza;Jan Ramon;Maurice Bruynooghe

166
Citations
A new ensemble coevolution system for detecting HIV-1 protein coevolution

Guangdi Li;Kristof Theys;Jens Verheyen;Andrea Clemencia Pineda-Peña;Andrea Clemencia Pineda-Peña

158
Citations
Frequent subgraph mining in outerplanar graphs

Tamás Horváth;Jan Ramon;Stefan Wrobel

136
Citations
Hierarchical multi-classification

Hendrik Blockeel;Maurice Bruynooghe;Sašo Džeroski;Jan Ramon

133
Citations
A polynomial time computable metric between point sets

Jan Ramon;Maurice Bruynooghe

124
Citations
Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner

Kurt Driessens;Jan Ramon;Hendrik Blockeel

119
Citations
Mining data from intensive care patients

Jan Ramon;Daan Fierens;Fabián Güiza;Geert Meyfroidt

116
Citations
Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling

Jan Ramon;Kurt Driessens;Tom Croonenborghs

109
Citations
Relational instance based regression for relational reinforcement learning

Kurt Driessens;Jan Ramon

103
Citations
Monte-Carlo Tree Search in Poker Using Expected Reward Distributions

Guy Broeck;Kurt Driessens;Jan Ramon

102
Citations
Relational instance based regression for relational reinforcement learning

Kurt Driessens;Jan Ramon

102
Citations
Graph kernels and Gaussian processes for relational reinforcement learning

Kurt Driessens;Jan Ramon;Thomas Gärtner

93
Citations
Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models.

Daan Fierens;Hendrik Blockeel;Maurice Bruynooghe;Jan Ramon

88
Citations
Logical bayesian networks and their relation to other probabilistic logical models

Daan Fierens;Hendrik Blockeel;Maurice Bruynooghe;Jan Ramon

88
Citations
A Framework for Defining Distances Between First-Order Logic Objects

Jan Ramon;Maurice Bruynooghe

77
Citations
Machine learning applications in proteomics research: How the past can boost the future

Pieter Kelchtermans;Pieter Kelchtermans;Wout Bittremieux;Kurt De Grave;Sven Degroeve

73
Citations
Executing Query Packs in ILP

Hendrik Blockeel;Luc Dehaspe;Bart Demoen;Gerda Janssens

72
Citations
Frequent subgraph mining in outerplanar graphs

Tamás Horváth;Jan Ramon;Stefan Wrobel

71
Citations

Frequent Co-Authors

Hendrik Blockeel KU Leuven

Maurice Bruynooghe KU Leuven

Luc De Raedt KU Leuven

Karl Tuyls DeepMind (United Kingdom)

Greet Van den Berghe KU Leuven

Lennart Martens Ghent University

Anne-Mieke Vandamme Rega Institute for Medical Research

Toon Calders University of Antwerp

Stefan Wrobel University of Bonn

Ross D. King University of Manchester

External Links

Personal website of Jan Ramon

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