Jim Laredo
Impact in
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- Mobile Crowdsensing and Crowdsourcing
- Open Source Software Innovations
- Software top 5%
- Software Reliability and Analysis Research
Papers in
- Software 7
- Software Reliability and Analysis Research 5
-
- Mobile Crowdsensing and Crowdsourcing 7
- Open Source Software Innovations 4
- Co-authors
- Vassilis KostakosJakob RogstadiusMaja VukovićAniket KitturBoris SmusMarin VukovićEvangelos KarapanosYunhui Zheng
- Journals
- IBM Journal of Research and Development (2 papers)ACM Transactions on Software Engineering and Methodology (1 paper)Empirical Software Engineering (1 paper)Communications of the ACM (1 paper)Information Services & Use (1 paper)
- Partner nations
- United StatesIndiaPortugal
In The Last Decade
Jim Laredo
36 papers receiving 635 citations
Peers
Comparison fields: 5 of 77
- Computer Science Applications 223
- Software 82
- Communication 133
- Information Systems 271
- Signal Processing 85
Countries citing papers authored by Jim Laredo
This map shows the geographic impact of Jim Laredo'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 Jim Laredo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jim Laredo more than expected).
Fields of papers citing papers by Jim Laredo
This network shows the impact of papers produced by Jim Laredo. 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 Jim Laredo. The network helps show where Jim Laredo may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jim Laredo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2023 | 7 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 0 | |
| 5 | 2022 | 2 | |
| 6 | 2021 | 3 | |
| 7 | 2021 | 86 | |
| 8 | 2018 | 27 | |
| 9 | 2014 | 3 | |
| 10 | Assessing service deployment readiness using enterprise crowdsourcing | 2013 | 3 |
| 11 | 2012 | 1 | |
| 12 | 2012 | 5 | |
| 13 | 2011 | 184 | |
| 14 | 2011 | 1 | |
| 15 | 2011 | 20 | |
| 16 | 2011 | 1 | |
| 17 | 2009 | 7 | |
| 18 | 2008 | 10 | |
| 19 | 2008 | 0 | |
| 20 | 2007 | 2 |
About Jim Laredo
Jim Laredo is a scholar working on Software, Computer Science Applications, Information Systems, Management Information Systems and Communication, having authored 39 papers that have together received 691 indexed citations. Recurring topics across this work include Service-Oriented Architecture and Web Services (16 papers), Software Engineering Research (9 papers), Business Process Modeling and Analysis (7 papers), Mobile Crowdsensing and Crowdsourcing (7 papers), Advanced Malware Detection Techniques (6 papers), Software Reliability and Analysis Research (5 papers), Software System Performance and Reliability (5 papers) and Open Source Software Innovations (4 papers). The work is most often cited by research in Computer Science Applications (223 citations), Software (82 citations), Communication (133 citations), Information Systems (271 citations) and Signal Processing (85 citations). Jim Laredo has collaborated with scholars based in United States, India and Portugal. Frequent co-authors include Vassilis Kostakos, Jakob Rogstadius, Maja Vuković, Aniket Kittur, Boris Smus, Marin Vuković, Evangelos Karapanos, Yunhui Zheng, Alessandro Morari and Edward S. Epstein. Their work appears in journals such as IBM Journal of Research and Development, ACM Transactions on Software Engineering and Methodology, Empirical Software Engineering, Communications of the ACM and Information Services & Use.
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.