Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
High-performance complex event processing over streams
2006525 citationsEugene Wu, Yanlei Diao et al.profile →
Fast and memory-efficient regular expression matching for deep packet inspection
2006342 citationsYu Fang, Zhifeng Chen et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Yanlei Diao'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 Yanlei Diao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yanlei Diao more than expected).
This network shows the impact of papers produced by Yanlei Diao. 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 Yanlei Diao. The network helps show where Yanlei Diao may publish in the future.
Co-authorship network of co-authors of Yanlei Diao
This figure shows the co-authorship network connecting the top 25 collaborators of Yanlei Diao.
A scholar is included among the top collaborators of Yanlei Diao 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 Yanlei Diao. Yanlei Diao is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Song, Fei, et al.. (2019). UDAO. Proceedings of the VLDB Endowment. 12(12). 1934–1937.2 indexed citations
5.
Papaemmanouil, Olga, et al.. (2016). Interactive Data Exploration via Machine Learning Models.. IEEE Data(base) Engineering Bulletin. 39. 38–46.15 indexed citations
6.
Diao, Yanlei, et al.. (2015). Building Highly-Optimized, Low-Latency Pipelines for Genomic Data Analysis. Conference on Innovative Data Systems Research.10 indexed citations
7.
Papaemmanouil, Olga, et al.. (2014). Explore-by-example. 517–528.86 indexed citations
Gyllstrom, Daniel, et al.. (2007). SASE: Complex Event Processing over Streams (Demo).. Conference on Innovative Data Systems Research. 407–411.17 indexed citations
16.
Fang, Yu, Zhifeng Chen, Yanlei Diao, T. V. Lakshman, & Randy H. Katz. (2006). Fast and memory-efficient regular expression matching for deep packet inspection. 93–102.342 indexed citations breakdown →
17.
Wu, Eugene, et al.. (2006). High-performance complex event processing over streams. 407–418.525 indexed citations breakdown →
Diao, Yanlei, et al.. (2000). Toward Learning Based Web Query Processing. Very Large Data Bases. 317–328.13 indexed citations
20.
Chen, Songting, et al.. (2000). FACT. 587–587.1 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.