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 Michael Luby'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 Michael Luby with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Luby more than expected).
This network shows the impact of papers produced by Michael Luby. 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 Michael Luby. The network helps show where Michael Luby may publish in the future.
Co-authorship network of co-authors of Michael Luby
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Luby.
A scholar is included among the top collaborators of Michael Luby 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 Michael Luby. Michael Luby is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Luby, Michael & Avi Wigderson. (2006). Pairwise Independence and Derandomization (Foundations and Trends(R) in Theoretical Computer Science). now publishers, Inc. eBooks.2 indexed citations
2.
Luby, Michael. (2003). Fast, Reliable Data Transport..14 indexed citations
Luby, Michael, Andrea Roli, & Marı́a Serna. (1997). Proceedings of the Second International Workshop on Randomization and Approximation Techniques in Computer Science.3 indexed citations
Albanese, Angela A., Johannes Blömer, Jeff Edmonds, Michael Luby, & Madhu Sudan. (1996). Priority encoding transmission. IEEE Transactions on Information Theory. 42(6). 1737–1744.375 indexed citations
8.
Dagum, Paul, Richard M. Karp, Michael Luby, & Sheldon M. Ross. (1995). An Optimal Algorithm for Monte Carlo Estimation (Extended Abstract).. 142–149.5 indexed citations
9.
Luby, Michael, et al.. (1995). PET - Priority Encoding Transmission: A New, Robust and Efficient Video Broadcast Technology (Video).. 547–548.7 indexed citations
10.
Alon, Noga, Jeff Edmonds, & Michael Luby. (1995). Linear Time Erasure Codes with Nearly Optimal Recovery (Extended Abstract).. 512–519.2 indexed citations
11.
Luby, Michael, Dana Randall, & Alistair Sinclair. (1995). Markov Chain Algorithms for Planar Lattice Structures (Extended Abstract).15 indexed citations
Ben-David, Shai, Benny Chor, Oded Goldreich, & Michael Luby. (1989). On the Theory of Average Case Complexity (abstract).. 36.2 indexed citations
17.
Impagliazzo, Russell & Michael Luby. (1989). One-way Functions are Essential for Complexity Based Cryptography (Extended Abstract). 230–235.19 indexed citations
18.
Luby, Michael, et al.. (1988). Steepest Descent Can Take Ex ponentia l T im e for Symmetric Connection Networks. Complex Systems. 2(2). 191–196.10 indexed citations
Lawler, Eugene L., et al.. (1983). Finding Shortest Paths in Very Large Networks.. 184–199.5 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.