Maosong Fu
Impact in
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- Advanced Database Systems and Queries
- IoT and Edge/Fog Computing
- Advanced Data Storage Technologies
- Distributed systems and fault tolerance
- Distributed and Parallel Computing Systems
- Information Systems top 1%
- Cloud Computing and Resource Management
Papers in
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- Peer-to-Peer Network Technologies 3
- Advanced Database Systems and Queries 2
- Software System Performance and Reliability 1
- Distributed systems and fault tolerance 1
- Advanced Data Storage Technologies 1
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- Cloud Computing and Resource Management 5
- Co-authors
- Karthik Ramasamy (3 shared papers)Sanjeev Kulkarni (2 shared papers)Jignesh M. Patel (2 shared papers)Dmitriy Ryaboy (1 shared paper)Jason Baird Jackson (1 shared paper)Amit K. Shukla (1 shared paper)Krishna Gade (1 shared paper)Christopher Kellogg (1 shared paper)
- Journals
- 2022 IEEE 38th International Conference on Data Engineering (ICDE) (1 paper)
- Partner nations
- United StatesUnited KingdomIsrael
In The Last Decade
Maosong Fu
6 papers receiving 976 citations
Maosong Fu's Hit Papers
Peers
Comparison fields: 5 of 50
- Computer Networks and Communications 854
- Information Systems 654
- Signal Processing 172
- Artificial Intelligence 326
- Hardware and Architecture 63
Countries citing papers authored by Maosong Fu
This map shows the geographic impact of Maosong Fu'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 Maosong Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maosong Fu more than expected).
Fields of papers citing papers by Maosong Fu
This network shows the impact of papers produced by Maosong Fu. 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 Maosong Fu. The network helps show where Maosong Fu may publish in the future.
Co-authors
The 21 scholars most cited alongside Maosong Fu, 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 | Storm@twitter Hit paper breakdown → | 2014 | 603 |
| 2 | Twitter Heron Hit paper breakdown → | 2015 | 368 |
| 3 | 2017 | 21 | |
| 4 | 2019 | 13 | |
| 5 | 2022 | 6 | |
| 6 | 2021 | 2 |
About Maosong Fu
Maosong Fu is a scholar working on Computer Networks and Communications, Information Systems, Information Systems and Management, Artificial Intelligence and Infectious Diseases, having authored 6 papers that have together received 1.0k indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (5 papers), Peer-to-Peer Network Technologies (3 papers), Advanced Database Systems and Queries (2 papers), Scientific Computing and Data Management (1 paper), Software System Performance and Reliability (1 paper), Distributed systems and fault tolerance (1 paper), Advanced Data Storage Technologies (1 paper) and Data Stream Mining Techniques (1 paper). The work is most often cited by research in Computer Networks and Communications (854 citations), Information Systems (654 citations), Signal Processing (172 citations), Artificial Intelligence (326 citations) and Hardware and Architecture (63 citations). Maosong Fu has collaborated with scholars based in United States, United Kingdom and Israel. Frequent co-authors include Karthik Ramasamy, Sanjeev Kulkarni, Jignesh M. Patel, Dmitriy Ryaboy, Jason Baird Jackson, Amit K. Shukla, Krishna Gade, Christopher Kellogg, Sriram Rao and Huijun Wu. Their work appears in journals such as 2022 IEEE 38th International Conference on Data Engineering (ICDE).
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.