Owen Conlan

2.7k total citations · 2 hit papers
135 papers, 1.1k citations indexed

About

Owen Conlan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Owen Conlan has authored 135 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Artificial Intelligence, 39 papers in Computer Vision and Pattern Recognition and 37 papers in Information Systems. Recurrent topics in Owen Conlan's work include Innovative Teaching and Learning Methods (25 papers), Semantic Web and Ontologies (22 papers) and Intelligent Tutoring Systems and Adaptive Learning (20 papers). Owen Conlan is often cited by papers focused on Innovative Teaching and Learning Methods (25 papers), Semantic Web and Ontologies (22 papers) and Intelligent Tutoring Systems and Adaptive Learning (20 papers). Owen Conlan collaborates with scholars based in Ireland, Austria and United Kingdom. Owen Conlan's co-authors include Vincent Wade, Declan Dagger, Dietrich Albert, Séamus Lawless, Cord Hockemeyer, Jane Walsh, David Lewis, Vincent Wade, Kalina Bontcheva and Francesco Ricci⋆ and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers & Education and Obesity Reviews.

In The Last Decade

Owen Conlan

127 papers receiving 982 citations

Hit Papers

Weight stigma experienced by patients with obesity in hea... 2023 2026 2024 2025 2023 2024 20 40 60

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Owen Conlan Ireland 17 368 324 320 249 152 135 1.1k
Stefanie Lindstaedt Austria 15 199 0.5× 105 0.3× 70 0.2× 223 0.9× 155 1.0× 106 821
Mike Wald United Kingdom 14 158 0.4× 102 0.3× 120 0.4× 129 0.5× 111 0.7× 92 880
Deborah A. Boehm‐Davis United States 21 248 0.7× 96 0.3× 131 0.4× 269 1.1× 157 1.0× 95 1.8k
Vania Dimitrova United Kingdom 18 375 1.0× 440 1.4× 270 0.8× 222 0.9× 108 0.7× 86 1.1k
Danial Hooshyar South Korea 22 438 1.2× 575 1.8× 462 1.4× 296 1.2× 115 0.8× 64 1.4k
Maiga Chang Canada 17 260 0.7× 304 0.9× 332 1.0× 371 1.5× 100 0.7× 134 1.1k
Barbara Di Eugenio United States 21 1.3k 3.5× 142 0.4× 194 0.6× 139 0.6× 131 0.9× 143 1.8k
Nigel Bosch United States 21 445 1.2× 470 1.5× 362 1.1× 206 0.8× 138 0.9× 78 1.6k
Manuel Freire Spain 17 230 0.6× 389 1.2× 504 1.6× 169 0.7× 129 0.8× 65 1.0k

Countries citing papers authored by Owen Conlan

Since Specialization
Citations

This map shows the geographic impact of Owen Conlan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Owen Conlan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Owen Conlan more than expected).

Fields of papers citing papers by Owen Conlan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Owen Conlan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Owen Conlan. The network helps show where Owen Conlan may publish in the future.

Co-authorship network of co-authors of Owen Conlan

This figure shows the co-authorship network connecting the top 25 collaborators of Owen Conlan. A scholar is included among the top collaborators of Owen Conlan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Owen Conlan. Owen Conlan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kay, Judy, et al.. (2024). Second Workshop on Context Representation in User Modelling. 225–228. 1 indexed citations
2.
Conlan, Owen, et al.. (2023). A Critical Analysis of EmpatheticDialogues as a Corpus for Empathetic Engagement. 1–6. 1 indexed citations
3.
Kay, Judy, et al.. (2023). 1st Workshop on Context Representation in User Modelling. Trinity's Access to Research Output (TARA) (Trinity College Dublin). 174–176. 1 indexed citations
4.
Steiner, Christina, et al.. (2017). Cultural Variations in E-Learning--A Case Study on Medical Training.. International journal on e-learning. 16(1). 81–98. 1 indexed citations
5.
Agosti, Maristella, et al.. (2014). Enriching Digital Cultural Heritage Collections via Annotations: The CULTURA approach.. Research Padua Archive (University of Padua). 319–326. 1 indexed citations
6.
Steiner, Christina, Adam Moore, Owen Conlan, et al.. (2013). An Investigation of Successful Self-Regulated-Learning in a Technology-Enhanced Learning Environment. 19–23. 2 indexed citations
7.
Conlan, Owen, et al.. (2013). CULTURA: Supporting Professional Humanities Researchers.. DH. 99–100. 1 indexed citations
8.
Lawless, Séamus, et al.. (2013). The CULTURA Portal: Exploring Cultural Treasures. Arrow@dit (Dublin Institute of Technology).
9.
Moore, Adam, Christina Steiner, & Owen Conlan. (2013). Design and development of an empirical smiley-based affective instrument. 41–52. 8 indexed citations
10.
Keeney, John, et al.. (2011). An ontology-driven approach to support wireless network monitoring for home area networks. 223–229. 5 indexed citations
11.
Dagger, Declan, Vincent Wade, & Owen Conlan. (2005). Personalisation for all: making adaptive course composition easy. Educational Technology & Society. 8(3). 9–25. 44 indexed citations
12.
Conlan, Owen, et al.. (2005). Towards the Dynamic Personalized Selection and Creation of Learning Objects. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2005(1). 1903–1909. 4 indexed citations
13.
Lawless, Séamus, Vincent Wade, & Owen Conlan. (2005). Dynamic Contextual eLearning - Dynamic Content Discovery, Capture and Learning Object Generation from Open Corpus Sources. Arrow@dit (Dublin Institute of Technology). 2005(1). 2158–2165. 2 indexed citations
14.
Conlan, Owen, et al.. (2005). Discrepancies Between Reality and Expectation: Can Adaptive Hypermedia Meet the Expectations of Teachers?. 88–95. 2 indexed citations
15.
Dagger, Declan, Owen Conlan, & Vincent Wade. (2005). Fundamental Requirements of Personalised eLearning Development Environments. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2005(1). 2746–2754. 4 indexed citations
16.
Conlan, Owen, et al.. (2004). Dynamic Composition and Personalization of PDA-based eLearning – Personalized mLearning. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2004(1). 234–242. 12 indexed citations
17.
Dagger, Declan, Vincent Wade, & Owen Conlan. (2004). A Framework for Developing Adaptive Personalized eLearning. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2004(1). 2579–2587. 2 indexed citations
18.
Dagger, Declan, Owen Conlan, & Vincent Wade. (2003). An Architecture for Candidacy in Adaptive eLearning Systems to Facilitate the Reuse of Learning Resources. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2003(1). 49–56. 26 indexed citations
19.
Dagger, Declan, Vincent Wade, & Owen Conlan. (2002). Towards a Standards-based Approach to e-Learning Personalization using Reusable Learning Objects. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2002(1). 210–217. 52 indexed citations
20.
Conlan, Owen, et al.. (2002). An Architecture for integrating Adaptive Hypermedia Services with Open Learning Environments. EdMedia: World Conference on Educational Media and Technology. 2002(1). 344–350. 15 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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