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.
Benchmarking cloud serving systems with YCSB
20102.4k citationsBrian F. Cooper, Adam Silberstein et al.profile →
MapReduce online
2010492 citationsTyson Condie, Neil Conway et al.profile →
Can machine learning be secure?
2006481 citationsMarco Barreno, Blaine Nelson et al.profile →
This map shows the geographic impact of Russell Sears'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 Russell Sears with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Russell Sears more than expected).
This network shows the impact of papers produced by Russell Sears. 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 Russell Sears. The network helps show where Russell Sears may publish in the future.
Co-authorship network of co-authors of Russell Sears
This figure shows the co-authorship network connecting the top 25 collaborators of Russell Sears.
A scholar is included among the top collaborators of Russell Sears 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 Russell Sears. Russell Sears is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
19 of 19 papers shown
1.
Gunawi, Haryadi S., et al.. (2018). Fail-Slow at Scale: Evidence of Hardware Performance Faults in Large Production Systems. 43. 1–14.5 indexed citations
2.
Davis, John D., J. R. Hayes, Ethan L. Miller, et al.. (2015). Purity. 1683–1694.46 indexed citations
3.
Chun, Byung-Gon, Tyson Condie, Carlo Curino, et al.. (2013). REEF. Proceedings of the VLDB Endowment. 6(12). 1370–1373.13 indexed citations
4.
Chen, Jianjun, et al.. (2012). Walnut. 743–754.24 indexed citations
5.
Chun, Byung-Gon, Carlo Curino, Russell Sears, et al.. (2012). Mobius: unified messaging and data serving for mobile apps. DSpace@MIT (Massachusetts Institute of Technology).1 indexed citations
6.
Chun, Byung-Gon, Carlo Curino, Russell Sears, et al.. (2012). Mobius. 141–154.22 indexed citations
Silberstein, Adam, Russell Sears, Wenchao Zhou, & Brian F. Cooper. (2011). A batch of PNUTS. 1101–1112.10 indexed citations
9.
Alvaro, Peter, Tyson Condie, Neil Conway, et al.. (2010). Boom analytics. 223–236.87 indexed citations
10.
Alvaro, Peter, Tyson Condie, Neil Conway, Joseph M. Hellerstein, & Russell Sears. (2010). I do declare. ACM SIGOPS Operating Systems Review. 43(4). 25–30.20 indexed citations
11.
Cooper, Brian F., et al.. (2010). Benchmarking cloud serving systems with YCSB. 143–154.2419 indexed citations breakdown →
12.
Condie, Tyson, Neil Conway, Peter Alvaro, et al.. (2010). MapReduce online. 21–21.492 indexed citations breakdown →
Alvaro, Peter, Tyson Condie, Neil Conway, et al.. (2009). BOOM: Data-Centric Programming in the Datacenter. UC Berkeley.13 indexed citations
15.
Alvaro, Peter, Tyson Condie, Neil Conway, Joseph M. Hellerstein, & Russell Sears. (2009). I Do Declare: Consensus in a Logic Language.1 indexed citations
16.
Sears, Russell, et al.. (2009). Segment-based recovery. Proceedings of the VLDB Endowment. 2(1). 490–501.7 indexed citations
17.
Sears, Russell, et al.. (2008). Rose. Proceedings of the VLDB Endowment. 1(1). 526–537.27 indexed citations
Barreno, Marco, Blaine Nelson, Russell Sears, Anthony D. Joseph, & J. D. Tygar. (2006). Can machine learning be secure?. 16–25.481 indexed citations breakdown →
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.