P.S. Yu
Impact in
- Software top 5%
- Model-Driven Software Engineering Techniques
- Development top 5%
- Software Engineering and Design Patterns
Papers in
-
- Algorithms and Data Compression 3
- Privacy-Preserving Technologies in Data 2
-
- Advanced Data Storage Technologies 4
- Distributed systems and fault tolerance 4
- Advanced Database Systems and Queries 2
- Optimization and Search Problems 1
- Co-authors
- Frank Budinsky (1 shared paper)John Vlissides (1 shared paper)S. Ma (1 shared paper)Kun‐Lung Wu (4 shared papers)Leon Stenneth (2 shared papers)Jiong Yang (1 shared paper)Jiawei Han (1 shared paper)Ming-Syan Chen⋆ (2 shared papers)
- Journals
- IEEE Transactions on Parallel and Distributed Systems (1 paper)IBM Systems Journal (1 paper)IEEE Transactions on Software Engineering (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)IEEE Transactions on Computers (1 paper)
- Partner nations
- United StatesTaiwanItaly
In The Last Decade
P.S. Yu
14 papers receiving 396 citations
Peers
Comparison fields: 5 of 66
- Software 85
- Development 62
- Artificial Intelligence 256
- Information Systems 176
- Computer Networks and Communications 115
Countries citing papers authored by P.S. Yu
This map shows the geographic impact of P.S. Yu'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 P.S. Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites P.S. Yu more than expected).
Fields of papers citing papers by P.S. Yu
This network shows the impact of papers produced by P.S. Yu. 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 P.S. Yu. The network helps show where P.S. Yu may publish in the future.
Co-authors
The 20 scholars most cited alongside P.S. Yu, 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 | 1996 | 173 | |
| 2 | 2004 | 80 | |
| 3 | 2006 | 50 | |
| 4 | 2002 | 27 | |
| 5 | 1992 | 24 | |
| 6 | 2018 | 19 | |
| 7 | 2010 | 16 | |
| 8 | 2010 | 14 | |
| 9 | 2003 | 12 | |
| 10 | 1994 | 9 | |
| 11 | 2002 | 5 | |
| 12 | 1988 | 3 | |
| 13 | 2003 | 2 | |
| 14 | 2002 | 2 |
About P.S. Yu
P.S. Yu is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Sociology and Political Science and Signal Processing, having authored 14 papers that have together received 436 indexed citations. Recurring topics across this work include Advanced Data Storage Technologies (4 papers), Distributed systems and fault tolerance (4 papers), Algorithms and Data Compression (3 papers), Multimedia Communication and Technology (2 papers), Privacy-Preserving Technologies in Data (2 papers), Advanced Database Systems and Queries (2 papers), Data Management and Algorithms (1 paper) and Optimization and Search Problems (1 paper). The work is most often cited by research in Software (85 citations), Development (62 citations), Artificial Intelligence (256 citations), Information Systems (176 citations) and Computer Networks and Communications (115 citations). P.S. Yu has collaborated with scholars based in United States, Taiwan and Italy. Frequent co-authors include Frank Budinsky, John Vlissides, S. Ma, Kun‐Lung Wu, Leon Stenneth, Jiong Yang, Jiawei Han, Ming-Syan Chen⋆, D.M. Dias and Bruno Ciciani. Their work appears in journals such as IEEE Transactions on Parallel and Distributed Systems, IBM Systems Journal, IEEE Transactions on Software Engineering, IEEE Transactions on Knowledge and Data Engineering and IEEE Transactions on Computers.
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.