Will Serrano
Impact in
- Media Technology top 5%
- Smart Cities and Technologies
- Transportation top 10%
- Human Mobility and Location-Based Analysis
Papers in
-
- Blockchain Technology Applications and Security 5
- Recommender Systems and Techniques 4
-
- Image Retrieval and Classification Techniques 3
- Co-authors
- Erol Gelenbe (4 shared papers)Philip Treleaven (2 shared papers)Yonghua Yin (1 shared paper)Elias Pimenidis (1 shared paper)Sumarga Kumar Sah Tyagi (1 shared paper)Sanjeev Jain (1 shared paper)
- Journals
- Neural Computing and Applications (4 papers)Neurocomputing (3 papers)Buildings (2 papers)Engineering Applications of Artificial Intelligence (1 paper)Smart Cities (1 paper)
- Partner nations
- United KingdomIndiaChina
In The Last Decade
Will Serrano
27 papers receiving 366 citations
Peers
Comparison fields: 5 of 79
- Media Technology 56
- Transportation 39
- Information Systems 128
- Computer Networks and Communications 82
- Building and Construction 48
Countries citing papers authored by Will Serrano
This map shows the geographic impact of Will Serrano'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 Will Serrano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Will Serrano more than expected).
Fields of papers citing papers by Will Serrano
This network shows the impact of papers produced by Will Serrano. 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 Will Serrano. The network helps show where Will Serrano may publish in the future.
Co-authors
The 6 scholars most cited alongside Will Serrano, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 94 | |
| 2 | 2020 | 64 | |
| 3 | 2018 | 23 | |
| 4 | 2022 | 20 | |
| 5 | 2021 | 18 | |
| 6 | 2021 | 16 | |
| 7 | 2019 | 14 | |
| 8 | 2022 | 13 | |
| 9 | 2021 | 13 | |
| 10 | 2022 | 13 | |
| 11 | 2019 | 12 | |
| 12 | 2018 | 12 | |
| 13 | 2023 | 10 | |
| 14 | 2019 | 10 | |
| 15 | 2017 | 9 | |
| 16 | 2024 | 8 | |
| 17 | 2017 | 7 | |
| 18 | 2023 | 6 | |
| 19 | 2017 | 4 | |
| 20 | 2019 | 4 |
About Will Serrano
Will Serrano is a scholar working on Information Systems, Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications and Electrical and Electronic Engineering, having authored 28 papers that have together received 385 indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (5 papers), Neural Networks and Applications (5 papers), Energy Load and Power Forecasting (4 papers), Stock Market Forecasting Methods (4 papers), IoT and Edge/Fog Computing (4 papers), Recommender Systems and Techniques (4 papers), Advanced Memory and Neural Computing (3 papers) and Image Retrieval and Classification Techniques (3 papers). The work is most often cited by research in Media Technology (56 citations), Transportation (39 citations), Information Systems (128 citations), Computer Networks and Communications (82 citations) and Building and Construction (48 citations). Will Serrano has collaborated with scholars based in United Kingdom, India and China. Frequent co-authors include Erol Gelenbe, Philip Treleaven, Yonghua Yin, Elias Pimenidis, Sumarga Kumar Sah Tyagi and Sanjeev Jain. Their work appears in journals such as Neural Computing and Applications, Neurocomputing, Buildings, Engineering Applications of Artificial Intelligence and Smart Cities.
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.