Konstantin Makarychev

3.5k total citations
68 papers, 1.2k citations indexed

About

Konstantin Makarychev is a scholar working on Computational Theory and Mathematics, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Konstantin Makarychev has authored 68 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Computational Theory and Mathematics, 21 papers in Computer Networks and Communications and 19 papers in Artificial Intelligence. Recurrent topics in Konstantin Makarychev's work include Complexity and Algorithms in Graphs (35 papers), Advanced Graph Theory Research (30 papers) and Optimization and Search Problems (12 papers). Konstantin Makarychev is often cited by papers focused on Complexity and Algorithms in Graphs (35 papers), Advanced Graph Theory Research (30 papers) and Optimization and Search Problems (12 papers). Konstantin Makarychev collaborates with scholars based in United States, United Kingdom and Israel. Konstantin Makarychev's co-authors include Yury Makarychev, Moses Charikar, Ishai Menache, Peter Bodík, Sriram Rao, Virajith Jalaparti, Matthew Caesar, Amit Agarwal, Assaf Naor and Nikolay Vereshchagin and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and IEEE Transactions on Information Theory.

In The Last Decade

Konstantin Makarychev

65 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Konstantin Makarychev United States 18 553 427 349 189 172 68 1.2k
Gregory B. Sorkin United States 19 481 0.9× 419 1.0× 345 1.0× 108 0.6× 49 0.3× 55 1.2k
Virginia Vassilevska Williams United States 18 853 1.5× 403 0.9× 472 1.4× 44 0.2× 73 0.4× 71 1.3k
Ömer Eğecioǧlu United States 18 271 0.5× 256 0.6× 289 0.8× 63 0.3× 271 1.6× 111 1.1k
René Peralta United States 14 328 0.6× 272 0.6× 612 1.8× 120 0.6× 78 0.5× 40 969
Richard Peng United States 20 549 1.0× 270 0.6× 437 1.3× 51 0.3× 47 0.3× 56 1.0k
Artur Czumaj Germany 20 511 0.9× 595 1.4× 415 1.2× 59 0.3× 61 0.4× 121 1.4k
Srinivasa Rao Satti South Korea 19 603 1.1× 749 1.8× 924 2.6× 80 0.4× 286 1.7× 70 1.6k
Yuri Rabinovich Israel 14 631 1.1× 325 0.8× 265 0.8× 40 0.2× 36 0.2× 38 1.2k
Luisa Gargano Italy 17 412 0.7× 547 1.3× 405 1.2× 61 0.3× 103 0.6× 88 1.1k
Michael Rodeh Israel 21 724 1.3× 819 1.9× 738 2.1× 135 0.7× 143 0.8× 46 1.8k

Countries citing papers authored by Konstantin Makarychev

Since Specialization
Citations

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

Fields of papers citing papers by Konstantin Makarychev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Konstantin Makarychev

This figure shows the co-authorship network connecting the top 25 collaborators of Konstantin Makarychev. A scholar is included among the top collaborators of Konstantin Makarychev 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 Konstantin Makarychev. Konstantin Makarychev 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.
Makarychev, Konstantin, et al.. (2023). Triplet Reconstruction and all other Phylogenetic CSPs are Approximation Resistant. 14. 253–284. 1 indexed citations
2.
Makarychev, Konstantin, et al.. (2023). Random Cuts are Optimal for Explainable k-Medians. 66890–66901.
3.
Makarychev, Konstantin, Miklós Z. Rácz, Cyrus Rashtchian, & Sergey Yekhanin. (2021). Batch Optimization for DNA Synthesis. 1949–1954. 5 indexed citations
4.
Makarychev, Konstantin, et al.. (2019). Correlation clustering with local objectives. neural information processing systems. 32. 9341–9350. 2 indexed citations
5.
Rashtchian, Cyrus, Konstantin Makarychev, Miklós Z. Rácz, et al.. (2017). Clustering Billions of Reads for DNA Data Storage. neural information processing systems. 30. 3360–3371. 22 indexed citations
6.
Makarychev, Konstantin, Yury Makarychev, Maxim Sviridenko, & Justin Ward. (2016). A Bi-Criteria Approximation Algorithm for k-Means. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 6 indexed citations
7.
Makarychev, Konstantin & Yury Makarychev. (2014). . Theory of Computing. 10(1). 341–358. 3 indexed citations
8.
Makarychev, Konstantin, Yury Makarychev, & Aravindan Vijayaraghavan. (2014). Bilu-linial stable instances of max cut and minimum multiway cut. Symposium on Discrete Algorithms. 890–906. 8 indexed citations
9.
Makarychev, Konstantin, Yury Makarychev, & Aravindan Vijayaraghavan. (2014). Algorithms for Semi-random Correlation Clustering.. 1 indexed citations
10.
Makarychev, Konstantin, Yury Makarychev, & Aravindan Vijayaraghavan. (2013). Bilu-Linial Stable Instances of Max Cut. arXiv (Cornell University). 1 indexed citations
11.
Buchbinder, Niv, et al.. (2013). Online Make-to-Order Joint Replenishment Model: Primal-Dual Competitive Algorithms. Operations Research. 61(4). 1014–1029. 11 indexed citations
12.
Makarychev, Konstantin, Yury Makarychev, & Aravindan Vijayaraghavan. (2012). Approximation algorithms for semi-random partitioning problems. 367–384. 15 indexed citations
13.
Kolla, Alexandra, Konstantin Makarychev, & Yury Makarychev. (2011). How to Play Unique Games Against a Semi-random Adversary: Study of Semi-random Models of Unique Games. 443–452. 9 indexed citations
14.
Cong, Guojing & Konstantin Makarychev. (2009). Improving Memory Access Locality for Large-Scale Graph Analysis Applications.. 121–127. 1 indexed citations
15.
Charikar, Moses, Konstantin Makarychev, & Yury Makarychev. (2007). Near-optimal algorithms for maximum constraint satisfaction problems. Symposium on Discrete Algorithms. 62–68. 17 indexed citations
16.
Charikar, Moses, Konstantin Makarychev, & Yury Makarychev. (2007). A divide and conquer algorithm for d-dimensional arrangement. Symposium on Discrete Algorithms. 541–546. 5 indexed citations
17.
Charikar, Moses, Konstantin Makarychev, & Yury Makarychev. (2006). Approximation Algorithm for the Max k-CSP Problem.. Electronic colloquium on computational complexity. 13(3). 344–8. 6 indexed citations
18.
Charikar, Moses, Konstantin Makarychev, & Yury Makarychev. (2006). Note on MAX 2SAT. Electronic colloquium on computational complexity. 13. 1 indexed citations
19.
Charikar, Moses, Konstantin Makarychev, & Yury Makarychev. (2006). Directed metrics and directed graph partitioning problems. Symposium on Discrete Algorithms. 51–60. 12 indexed citations
20.
Alon, Ilan, Konstantin Makarychev, Yury Makarychev, & Assaf Naor. (2005). Quadratic forms on graphs. Inventiones mathematicae. 163(3). 499–522. 48 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.

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