Damien Fay
- Electrical and Electronic Engineering
- Statistical and Nonlinear Physics top 5%
- Computer Networks and Communications top 10%
- Artificial Intelligence top 10%
- Building and Construction top 10%
- Co-authors
- John V. RingwoodBogdan GabryśAndrew W. MooreHamed HaddadiJérôme KunegisSteve UhligRichard MortierAlmerima Jamakovic
- Topics
- Complex Network Analysis Techniques (11 papers)Energy Load and Power Forecasting (8 papers)Fault Detection and Control Systems (4 papers)
- Partner nations
- United KingdomIrelandGermany
In The Last Decade
Damien Fay
36 papers receiving 437 citations
Peers
Comparison fields: 5 of 80
- Electrical and Electronic Engineering 134
- Statistical and Nonlinear Physics 114
- Computer Networks and Communications 100
- Artificial Intelligence 97
- Building and Construction 51
Countries citing papers authored by Damien Fay
This map shows the geographic impact of Damien Fay'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 Damien Fay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Damien Fay more than expected).
Fields of papers citing papers by Damien Fay
This network shows the impact of papers produced by Damien Fay. 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 Damien Fay. The network helps show where Damien Fay may publish in the future.
Co-authorship network of co-authors of Damien Fay
This figure shows the co-authorship network connecting the top 25 collaborators of Damien Fay. A scholar is included among the top collaborators of Damien Fay 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 Damien Fay. Damien Fay is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 13 | |
| 3 | 6 | |
| 4 | 10 | |
| 5 | 8 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 9 | |
| 9 | 2 | |
| 10 | 77 | |
| 11 | 23 | |
| 12 | On the importance of local connectivity for Internet topology models | 16 |
| 13 | 25 | |
| 14 | 51 | |
| 15 | 9 | |
| 16 | 0 | |
| 17 | Forecasting Electricity Load and Prices in an Algerian Deregulated Market | 1 |
| 18 | 32 | |
| 19 | Establishing a Solution Strategy for Electrical Demand Forecasting in Ireland | 5 |
| 20 | Comparative linear and neural parallel forecasting models for short-term Irish electricity load | 0 |
About Damien Fay
Damien Fay is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Management Science and Operations Research, having authored 39 papers that have together received 454 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (11 papers), Energy Load and Power Forecasting (8 papers) and Fault Detection and Control Systems (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (114 citations), Computer Networks and Communications (100 citations) and Developmental Biology (9 citations). Damien Fay has collaborated with scholars based in United Kingdom, Ireland and Germany. Frequent co-authors include John V. Ringwood, Bogdan Gabryś, Andrew W. Moore, Hamed Haddadi, Jérôme Kunegis, Steve Uhlig, Richard Mortier, Almerima Jamakovic, Marissa Condon and Kenneth N. Brown. Their work appears in journals such as IEEE Transactions on Power Systems, Neurocomputing and IEEE/ACM Transactions on Networking.
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.