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.
This map shows the geographic impact of Guy L. Steele'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 Guy L. Steele with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guy L. Steele more than expected).
This network shows the impact of papers produced by Guy L. Steele. 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 Guy L. Steele. The network helps show where Guy L. Steele may publish in the future.
Co-authorship network of co-authors of Guy L. Steele
This figure shows the co-authorship network connecting the top 25 collaborators of Guy L. Steele.
A scholar is included among the top collaborators of Guy L. Steele 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 Guy L. Steele. Guy L. Steele is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zaheer, Manzil, Michael Wick, Jean-Baptiste Tristan, Alexander J. Smola, & Guy L. Steele. (2016). Exponential Stochastic Cellular Automata for Massively Parallel Inference. International Conference on Artificial Intelligence and Statistics. 966–975.15 indexed citations
5.
Tristan, Jean-Baptiste, Joseph Tassarotti, & Guy L. Steele. (2015). Efficient Training of LDA on a GPU by Mean-for-Mode Estimation. International Conference on Machine Learning. 59–68.10 indexed citations
6.
Gosling, James, Bill Joy, Guy L. Steele, Gilad Bracha, & Alex Buckley. (2013). The Java Language Specification, Java SE 8 Edition.114 indexed citations
Gosling, James, Bill Joy, Guy L. Steele, & Gilad Bracha. (2005). Java(TM) Language Specification, The (3rd Edition) (Java (Addison-Wesley)).389 indexed citations
Detlefs, David, Paul Martin, Mark Moir, & Guy L. Steele. (2002). Lock-free reference counting. Distributed Computing. 15(4). 255–271.49 indexed citations
11.
Agesen, Ole, David Detlefs, Christine H. Flood, et al.. (2002). \bf DCAS-Based Concurrent Deques. Theory of Computing Systems. 35(3). 349–386.15 indexed citations
12.
Gosling, James, Bill Joy, Guy L. Steele, & Gilad Bracha. (2000). Java Language Specification, Second Edition: The Java Series. Addison-Wesley Longman Publishing Co., Inc. eBooks.280 indexed citations
13.
Boehm, Hans‐J. & Guy L. Steele. (1996). Proceedings of the 23rd ACM SIGPLAN-SIGACT symposium on Principles of programming languages.22 indexed citations
14.
Steele, Guy L., et al.. (1995). C, a reference manual (4th ed.). Prentice-Hall, Inc eBooks.8 indexed citations
15.
Harbison, Samuel P. & Guy L. Steele. (1994). C: A Reference Manual, Fourth Edition. Prentice Hall PTR eBooks.5 indexed citations
Boyer, Robert S., et al.. (1984). Proceedings of the 1984 ACM Symposium on LISP and functional programming.22 indexed citations
20.
Brooks, Rodney A., Richard P. Gabriel, & Guy L. Steele. (1983). Lisp-in-lisp: high performance and portability. International Joint Conference on Artificial Intelligence. 845–849.2 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.