David Lillis

966 total citations
33 papers, 266 citations indexed

About

David Lillis is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, David Lillis has authored 33 papers receiving a total of 266 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 11 papers in Information Systems and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in David Lillis's work include Multi-Agent Systems and Negotiation (6 papers), Topic Modeling (6 papers) and Service-Oriented Architecture and Web Services (6 papers). David Lillis is often cited by papers focused on Multi-Agent Systems and Negotiation (6 papers), Topic Modeling (6 papers) and Service-Oriented Architecture and Web Services (6 papers). David Lillis collaborates with scholars based in Ireland, United Kingdom and China. David Lillis's co-authors include Paul Nulty, Congcong Wang, Rem Collier, Mark Scanlon, G. M. P. O’Hare, Xiaoyu Du, John Dunnion, Fergus Toolan, Eoin O’Neill and Zhen Yang and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Machine Learning.

In The Last Decade

David Lillis

32 papers receiving 253 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David Lillis Ireland	9	142	109	46	46	40	33	266
Claus Atzenbeck Denmark	9	94 0.7×	65 0.6×	71 1.5×	20 0.4×	30 0.8×	62	273
Leo Gao Canada	4	359 2.5×	94 0.9×	68 1.5×	21 0.5×	27 0.7×	4	469
Stephen Macke United States	6	104 0.7×	94 0.9×	33 0.7×	7 0.2×	26 0.7×	8	237
Ashwin Paranjape United States	4	195 1.4×	54 0.5×	39 0.8×	9 0.2×	26 0.7×	7	325
Ally S. Nyamawe Tanzania	10	82 0.6×	158 1.4×	11 0.2×	43 0.9×	66 1.6×	27	264
Youn Kyu Lee South Korea	9	116 0.8×	182 1.7×	44 1.0×	78 1.7×	91 2.3×	47	296
Wanjun Zhong China	11	411 2.9×	155 1.4×	65 1.4×	23 0.5×	12 0.3×	36	543
Xinxi Lyu United States	4	370 2.6×	60 0.6×	107 2.3×	18 0.4×	25 0.6×	4	490
April Yi Wang United States	9	98 0.7×	108 1.0×	84 1.8×	20 0.4×	21 0.5×	21	280
Vitaly Klyuev Japan	10	171 1.2×	137 1.3×	26 0.6×	75 1.6×	101 2.5×	47	291

Countries citing papers authored by David Lillis

Since Specialization

Citations

This map shows the geographic impact of David Lillis'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 David Lillis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Lillis more than expected).

Fields of papers citing papers by David Lillis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Lillis. 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 David Lillis. The network helps show where David Lillis may publish in the future.

Co-authorship network of co-authors of David Lillis

This figure shows the co-authorship network connecting the top 25 collaborators of David Lillis. A scholar is included among the top collaborators of David Lillis 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 David Lillis. David Lillis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Lillis, David, et al.. (2024). A neural meta model for predicting winter wheat crop yield. Machine Learning. 113(6). 3771–3788. 3 indexed citations

Lillis, David. (2023). Use R for data analysis and research. 68(2). 73–79. 3 indexed citations

Johnston, Michael & David Lillis. (2023). Statistical modelling and analysis of NCEA and New Zealand Scholarship assessment data. 68(4). 126–135.

Nulty, Paul, et al.. (2023). Argument Mining with Graph Representation Learning. 371–380. 3 indexed citations

Nulty, Paul, et al.. (2022). Enhancing Legal Argument Mining with Domain Pre-training and Neural Networks. SHILAP Revista de lepidopterología. NLP4DH. 9 indexed citations

Nulty, Paul & David Lillis. (2020). The UCD-Net System at SemEval-2020 Task 1: Temporal Referencing with Semantic Network Distances. Research Repository UCD (University College Dublin). 119–125. 3 indexed citations

Li, Tong, Shiheng Wang, David Lillis, & Zhen Yang. (2020). Combining Machine Learning and Logical Reasoning to Improve Requirements Traceability Recovery. Applied Sciences. 10(20). 7253–7253. 19 indexed citations

Lillis, David. (2020). On the Evaluation of Data Fusion for Information Retrieval. Research Repository UCD (University College Dublin). 54–57. 3 indexed citations

Wang, Congcong & David Lillis. (2019). Classification for Crisis-Related Tweets Leveraging Word Embeddings and Data Augmentation.. Research Repository UCD (University College Dublin). 7 indexed citations

10.

Collier, Rem, Eoin O’Neill, David Lillis, & G. M. P. O’Hare. (2019). MAMS: Multi-Agent MicroServices✱. Research Repository UCD (University College Dublin). 655–662. 20 indexed citations

11.

Lillis, David, et al.. (2019). Improving the accuracy of automated facial age estimation to aid CSEM investigations. Digital Investigation. 28. S142–S142. 4 indexed citations

12.

Pan, Xingyu, et al.. (2018). CodEX: Source Code Plagiarism Detection Based on Abstract Syntax Tree.. 362–373. 7 indexed citations

13.

Matheus, Christopher J., Aidan Boran, Rem Collier, et al.. (2018). Semantic network management for next‐generation networks. Computational Intelligence. 35(2). 285–309. 2 indexed citations

14.

Scanlon, Mark, Xiaoyu Du, & David Lillis. (2017). EviPlant: An efficient digital forensic challenge creation, manipulation and distribution solution. Digital Investigation. 20. S29–S36. 19 indexed citations

15.

O’Grady, Michael J., et al.. (2013). Pervasive Sensing: Addressing the Heterogeneity Problem. Journal of Physics Conference Series. 450. 12044–12044. 1 indexed citations

16.

Dragone, Mauro, et al.. (2011). Separation of concerns in hybrid component and agent systems. International Journal of Communication Networks and Distributed Systems. 6(2). 176–176. 1 indexed citations

17.

Lillis, David & Rem Collier. (2010). ACRE: Agent Communication Reasoning Engine.. 1 indexed citations

18.

Lillis, David, Rem Collier, Mauro Dragone, & G. M. P. O’Hare. (2009). An agent-based approach to component management. Arrow@dit (Dublin Institute of Technology). 529–536. 1 indexed citations

19.

Lillis, David, Fergus Toolan, Rem Collier, & John Dunnion. (2008). Extending probabilistic data fusion using sliding windows. 358–369. 7 indexed citations

20.

Lillis, David, Fergus Toolan, Rem Collier, & John Dunnion. (2006). Probabilistic data fusion on a large document collection. Artificial Intelligence Review. 26(1-2). 23–34. 2 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.

Explore authors with similar magnitude of impact