David Lillis
Impact in
Papers in
-
- Multi-Agent Systems and Negotiation 6
- Topic Modeling 6
- Natural Language Processing Techniques 3
- Advanced Software Engineering Methodologies 3
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- Service-Oriented Architecture and Web Services 6
- Software Engineering Research 3
- Co-authors
- Paul Nulty (4 shared papers)Congcong Wang (3 shared papers)Rem Collier (13 shared papers)Mark Scanlon (3 shared papers)G. M. P. O’Hare (7 shared papers)John Dunnion (4 shared papers)Fergus Toolan (4 shared papers)Xiaoyu Du (1 shared paper)
- Journals
- Artificial Intelligence Review (2 papers)Digital Investigation (2 papers)IEEE Access (1 paper)Machine Learning (1 paper)Applied Sciences (1 paper)
- Partner nations
- IrelandUnited KingdomChina
In The Last Decade
David Lillis
32 papers receiving 253 citations
Peers
Comparison fields: 5 of 70
- Health Informatics 10
- Software 20
- Information Systems 109
- Artificial Intelligence 142
- Signal Processing 46
Countries citing papers authored by David Lillis
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
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-authors
The 25 scholars most cited alongside David Lillis, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 61 | |
| 2 | 2019 | 20 | |
| 3 | 2020 | 19 | |
| 4 | 2017 | 19 | |
| 5 | 2018 | 17 | |
| 6 | 2010 | 16 | |
| 7 | 2024 | 14 | |
| 8 | 2009 | 11 | |
| 9 | 2022 | 9 | |
| 10 | CodEX: Source Code Plagiarism Detection Based on Abstract Syntax Tree. | 2018 | 7 |
| 11 | Classification for Crisis-Related Tweets Leveraging Word Embeddings and Data Augmentation. | 2019 | 7 |
| 12 | 2008 | 7 | |
| 13 | 2024 | 6 | |
| 14 | 2013 | 5 | |
| 15 | 2023 | 5 | |
| 16 | 2019 | 4 | |
| 17 | 2022 | 4 | |
| 18 | 2007 | 4 | |
| 19 | 2024 | 3 | |
| 20 | 2023 | 3 |
About David Lillis
David Lillis is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Signal Processing and Computer Networks and Communications, having authored 33 papers that have together received 266 indexed citations. Recurring topics across this work include Service-Oriented Architecture and Web Services (6 papers), Multi-Agent Systems and Negotiation (6 papers), Topic Modeling (6 papers), Data Management and Algorithms (5 papers), Software System Performance and Reliability (4 papers), Natural Language Processing Techniques (3 papers), Advanced Software Engineering Methodologies (3 papers) and Software Engineering Research (3 papers). The work is most often cited by research in Health Informatics (10 citations), Software (20 citations), Information Systems (109 citations), Artificial Intelligence (142 citations) and Signal Processing (46 citations). David Lillis has collaborated with scholars based in Ireland, United Kingdom and China. Frequent co-authors include Paul Nulty, Congcong Wang, Rem Collier, Mark Scanlon, G. M. P. O’Hare, John Dunnion, Fergus Toolan, Xiaoyu Du, Tong Li and Eoin O’Neill. Their work appears in journals such as Artificial Intelligence Review, Digital Investigation, IEEE Access, Machine Learning and Applied Sciences.
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.