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.
Summarizing Source Code using a Neural Attention Model
2016415 citationsSrinivasan Iyer, Ioannis Konstas 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 Alvin Cheung'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 Alvin Cheung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alvin Cheung more than expected).
This network shows the impact of papers produced by Alvin Cheung. 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 Alvin Cheung. The network helps show where Alvin Cheung may publish in the future.
Co-authorship network of co-authors of Alvin Cheung
This figure shows the co-authorship network connecting the top 25 collaborators of Alvin Cheung.
A scholar is included among the top collaborators of Alvin Cheung 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 Alvin Cheung. Alvin Cheung is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Yan, Cong, et al.. (2020). View-Driven Optimization of Database-Backed Web Applications.. Conference on Innovative Data Systems Research.1 indexed citations
7.
Haynes, Brandon, et al.. (2020). VisualWorldDB: A DBMS for the Visual World.. Conference on Innovative Data Systems Research.5 indexed citations
Cheung, Alvin, Mihai Budiu, Changhoon Kim, et al.. (2016). Packet Transactions: High-Level Programming for Line-Rate Switches. DSpace@MIT (Massachusetts Institute of Technology).2 indexed citations
14.
Kamil, Shoaib, Alvin Cheung, Shachar Itzhaky, & Armando Solar-Lezama. (2016). Verified lifting of stencil computations. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 711–726.34 indexed citations
15.
Cheung, Alvin. (2015). Towards Generating Application-Specific Data Management Systems.. Conference on Innovative Data Systems Research.1 indexed citations
16.
Cheung, Alvin, et al.. (2014). Using Program Analysis to Improve Database Applications.. IEEE Data(base) Engineering Bulletin. 37. 48–59.14 indexed citations
17.
Cheung, Alvin, et al.. (2013). StatusQuo: Making Familiar Abstractions Perform Using Program Analysis. Conference on Innovative Data Systems Research.17 indexed citations
18.
Hui, Sam K., et al.. (2010). International Real Estate Review. International Real Estate Review. 13(1). 1–29.9 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.