Luca Trevisan

7.3k citations
117 papers · 2.5k indexed · h-index 28

Luca Trevisan

112 papers receiving 2.2k citations

Peers

Luca Trevisan
Comparison fields: 5 of 80
  • Computational Theory and Mathematics 1.8k
  • Computer Graphics and Computer-Aided Design 218
  • Artificial Intelligence 1.3k
  • Discrete Mathematics and Combinatorics 127
  • Computer Networks and Communications 677
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Muli Safra Israel
Robert Krauthgamer Israel
Ronitt Rubinfeld United States
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Citations per year

Countries citing papers authored by Luca Trevisan

Since Specialization
Citations

This map shows the geographic impact of Luca Trevisan'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 Luca Trevisan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luca Trevisan more than expected).

Fields of papers citing papers by Luca Trevisan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luca Trevisan. 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 Luca Trevisan. The network helps show where Luca Trevisan may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Luca Trevisan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Luca Trevisan Line = papers co-authored together Luca Trevisan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1
Friend or Foe? Population Protocols can perform Community Detection
20171
2 20174
3 20169
4
20152
5
Simple Dynamics for Majority Consensus
20131
6
Theory and Applications of Models of Computation : 10th International Conference, TAMC 2013, Hong Kong, China, May 20-22, 2013. Proceedings
20132
7
Improved Pseudorandom Generators for Depth 2 Circuits.
20092
8
Non-uniform attacks against one-way functions and PRGs.
20092
9
200818
10
Pseudorandom Walks in Biregular Graphs and the RL vs. L Problem
20056
11 20051
12
Lecture Notes on Computational Complexity
20045
13
On epsilon-Biased Generators in NC0
20036
14 20010
15
Lower Bounds on the Efficiency of Generic Cryptographic Constructions
20001
16
Recycling Queries in PCPs and in Linearity Tests
199812
17
Constructions of Near-Optimal Extractors Using Pseudo-Random Generators
199813
18
Recent Advances Towards Proving P = BPP.
199811
19
A tight characterization of NP with 3 query PCPs
19983
20
Gadgets, Approximation, and Linear Programming (extended abstract).
19966

About Luca Trevisan

Luca Trevisan is a scholar working on Computational Theory and Mathematics, Discrete Mathematics and Combinatorics and Artificial Intelligence, having authored 117 papers that have together received 2.5k indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (66 papers), Advanced Graph Theory Research (34 papers), Cryptography and Data Security (32 papers), Machine Learning and Algorithms (21 papers), Optimization and Search Problems (12 papers), semigroups and automata theory (11 papers), Coding theory and cryptography (10 papers) and Algorithms and Data Compression (9 papers). The work is most often cited by research in Computational Theory and Mathematics (1.8k citations), Computer Graphics and Computer-Aided Design (218 citations) and Artificial Intelligence (1.3k citations). Luca Trevisan has collaborated with scholars based in United States, Italy and Israel. Frequent co-authors include Salil Vadhan, Madhu Sudan, Alex Samorodnitsky, Jonathan Katz, Shayan Oveis Gharan, David P. Williamson, Andrej Bogdanov, Oded Goldreich, James R. Lee and Andrea Clementi. Their work appears in journals such as Journal of the ACM, SIAM Journal on Computing and Theoretical Computer Science.

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.

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