P.S. Yu

813 total citations
14 papers, 436 citations indexed

About

P.S. Yu is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, P.S. Yu has authored 14 papers receiving a total of 436 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Computer Networks and Communications and 3 papers in Information Systems. Recurrent topics in P.S. Yu's work include Distributed systems and fault tolerance (4 papers), Advanced Data Storage Technologies (4 papers) and Algorithms and Data Compression (3 papers). P.S. Yu is often cited by papers focused on Distributed systems and fault tolerance (4 papers), Advanced Data Storage Technologies (4 papers) and Algorithms and Data Compression (3 papers). P.S. Yu collaborates with scholars based in United States, Italy and Canada. P.S. Yu's co-authors include John Vlissides, Frank Budinsky, S. Ma, Kun‐Lung Wu, Jiong Yang, Jiawei Han, Ming-Syan Chen⋆, Leon Stenneth, Bruno Ciciani and D.M. Dias and has published in prestigious journals such as IEEE Transactions on Software Engineering, IEEE Transactions on Knowledge and Data Engineering and IEEE Transactions on Computers.

In The Last Decade

P.S. Yu

14 papers receiving 396 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
P.S. Yu United States 10 256 176 115 85 62 14 436
Gerard Meszaros United States 8 203 0.8× 438 2.5× 165 1.4× 302 3.6× 97 1.6× 19 611
Duane Hybertson United States 7 199 0.8× 324 1.8× 120 1.0× 62 0.7× 19 0.3× 16 478
Claudia Raibulet Italy 11 257 1.0× 340 1.9× 204 1.8× 101 1.2× 11 0.2× 80 497
Cay S. Horstmann United States 11 108 0.4× 102 0.6× 84 0.7× 47 0.6× 17 0.3× 43 348
Nan C. Shu United States 7 128 0.5× 109 0.6× 176 1.5× 57 0.7× 9 0.1× 16 389
David S. Kosbie United States 5 148 0.6× 114 0.6× 92 0.8× 82 1.0× 11 0.2× 14 449
Andrew Mickish United States 4 163 0.6× 120 0.7× 97 0.8× 94 1.1× 10 0.2× 6 474
Jeromy Carrière United States 6 266 1.0× 295 1.7× 158 1.4× 87 1.0× 7 0.1× 8 445
Alan W. Brown United States 14 278 1.1× 350 2.0× 135 1.2× 129 1.5× 7 0.1× 28 571
Joshua Bloch United States 8 270 1.1× 289 1.6× 263 2.3× 145 1.7× 8 0.1× 14 646

Countries citing papers authored by P.S. Yu

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of P.S. Yu

This figure shows the co-authorship network connecting the top 25 collaborators of P.S. Yu. A scholar is included among the top collaborators of P.S. Yu 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 P.S. Yu. P.S. Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Huang, He, Bokai Cao, P.S. Yu, Chang‐Dong Wang, & Alex Leow. (2018). dpMood: Exploiting Local and Periodic Typing Dynamics for Personalized Mood Prediction. 157–166. 19 indexed citations
2.
Stenneth, Leon, P.S. Yu, & Ouri Wolfson. (2010). Mobile systems location privacy: “MobiPriv” a robust k anonymous system. 54–63. 14 indexed citations
4.
Han, Jiawei, et al.. (2006). Efficient classification across multiple database relations: a CrossMine approach. IEEE Transactions on Knowledge and Data Engineering. 18(6). 770–783. 50 indexed citations
5.
Yu, P.S., et al.. (2004). Is random model better? On its accuracy and efficiency. 51–58. 80 indexed citations
6.
Wu, Kun‐Lung, Shyh-Kwei Chen, & P.S. Yu. (2003). Dynamic refinement of table summarization for M-commerce. 179–186. 2 indexed citations
7.
Chen⋆, Ming-Syan, P.S. Yu, & Kun‐Lung Wu. (2003). Scheduling and processor allocation for parallel execution of multijoin queries. 724. 58–67. 12 indexed citations
8.
Chen⋆, Ming-Syan, P.S. Yu, & Kun‐Lung Wu. (2002). Indexed sequential data broadcasting in wireless mobile computing. NTUR (臺灣機構典藏). 124–131. 27 indexed citations
9.
Lo, Ming-Ling, Kun‐Lung Wu, & P.S. Yu. (2002). TabSum: a flexible and dynamic table summarization approach. 628–635. 5 indexed citations
10.
Dan, A. & P.S. Yu. (2002). Performance comparisons of buffer coherency policies. 75. 208–217. 2 indexed citations
11.
Budinsky, Frank, et al.. (1996). Automatic code generation from design patterns. IBM Systems Journal. 35(2). 151–171. 173 indexed citations
12.
Leff, Avraham & P.S. Yu. (1994). A performance study of robust distributed load sharing strategies. IEEE Transactions on Parallel and Distributed Systems. 5(12). 1286–1301. 9 indexed citations
13.
Ciciani, Bruno, D.M. Dias, & P.S. Yu. (1992). Analysis of concurrency-coherency control protocols for distributed transaction processing systems with regional locality. IEEE Transactions on Software Engineering. 18(10). 899–914. 24 indexed citations
14.
Yu, P.S., et al.. (1988). Optimal design and sequential analysis of VLSI testing strategy. IEEE Transactions on Computers. 37(3). 339–347. 3 indexed citations

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.

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