David Gamarnik

3.6k total citations
104 papers, 1.5k citations indexed

About

David Gamarnik is a scholar working on Computational Theory and Mathematics, Statistics and Probability and Computer Networks and Communications. According to data from OpenAlex, David Gamarnik has authored 104 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Computational Theory and Mathematics, 32 papers in Statistics and Probability and 28 papers in Computer Networks and Communications. Recurrent topics in David Gamarnik's work include Advanced Queuing Theory Analysis (27 papers), Markov Chains and Monte Carlo Methods (26 papers) and Complexity and Algorithms in Graphs (20 papers). David Gamarnik is often cited by papers focused on Advanced Queuing Theory Analysis (27 papers), Markov Chains and Monte Carlo Methods (26 papers) and Complexity and Algorithms in Graphs (20 papers). David Gamarnik collaborates with scholars based in United States, Canada and United Kingdom. David Gamarnik's co-authors include Dimitris Bertsimas, John N. Tsitsiklis, Ross Anderson, Itai Ashlagi, Antar Bandyopadhyay, Madhu Sudan, Don Coppersmith, Maxim Sviridenko, Mohsen Bayati and Prasad Tetali and has published in prestigious journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Automatic Control and IEEE Transactions on Information Theory.

In The Last Decade

David Gamarnik

95 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Gamarnik United States 23 496 421 337 322 280 104 1.5k
Arie Hordijk Netherlands 26 559 1.1× 446 1.1× 1.0k 3.1× 431 1.3× 324 1.2× 119 2.1k
Guy Fayolle France 16 630 1.3× 160 0.4× 600 1.8× 244 0.8× 76 0.3× 56 1.3k
Leopold Flatto United States 19 329 0.7× 194 0.5× 391 1.2× 138 0.4× 109 0.4× 74 1.3k
Claire Kenyon France 21 571 1.2× 364 0.9× 58 0.2× 173 0.5× 280 1.0× 55 1.4k
Anatolii A. Puhalskii Russia 19 432 0.9× 139 0.3× 617 1.8× 289 0.9× 267 1.0× 38 1.6k
Sergey Foss Russia 23 485 1.0× 149 0.4× 602 1.8× 504 1.6× 196 0.7× 108 1.9k
Adam Shwartz Israel 20 554 1.1× 192 0.5× 483 1.4× 201 0.6× 385 1.4× 63 1.6k
Mohsen Bayati United States 24 393 0.8× 138 0.3× 81 0.2× 272 0.8× 487 1.7× 60 1.7k
Johan S. H. van Leeuwaarden Netherlands 19 499 1.0× 88 0.2× 693 2.1× 233 0.7× 45 0.2× 159 1.4k
Gerard Hooghiemstra Netherlands 18 251 0.5× 167 0.4× 126 0.4× 197 0.6× 82 0.3× 68 1.0k

Countries citing papers authored by David Gamarnik

Since Specialization
Citations

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

Fields of papers citing papers by David Gamarnik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Gamarnik

This figure shows the co-authorship network connecting the top 25 collaborators of David Gamarnik. A scholar is included among the top collaborators of David Gamarnik 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 David Gamarnik. David Gamarnik 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.
Alaoui, A. El & David Gamarnik. (2025). Hardness of Sampling Solutions From the Symmetric Binary Perceptron. Random Structures and Algorithms. 66(4).
2.
Anschuetz, Eric R., David Gamarnik, & Bobak T. Kiani. (2024). Combinatorial NLTS From the Overlap Gap Property. Quantum. 8. 1527–1527.
3.
Gamarnik, David, Mihyun Kang, & Paweł Prałat. (2024). Cliques, Chromatic Number, and Independent Sets in the Semi-random Process. SIAM Journal on Discrete Mathematics. 38(3). 2312–2334. 2 indexed citations
4.
Gamarnik, David, et al.. (2022). The Random Number Partitioning Problem: Overlap Gap Property and Algorithmic Barriers. 2022 IEEE International Symposium on Information Theory (ISIT). 778–783. 1 indexed citations
5.
Gamarnik, David, et al.. (2018). High Dimensional Linear Regression using Lattice Basis Reduction. Neural Information Processing Systems. 31. 1842–1852.
6.
Gamarnik, David, et al.. (2018). Computing the partition function of the Sherrington-Kirkpatrick model is hard on average. arXiv (Cornell University). 6 indexed citations
7.
Anderson, Ross, Itai Ashlagi, David Gamarnik, & Yash Kanoria. (2017). Efficient Dynamic Barter Exchange. Operations Research. 65(6). 1446–1459. 55 indexed citations
8.
Gamarnik, David, Quan Li, & Hongyi Zhang. (2017). Matrix Completion from $O(n)$ Samples in Linear Time.. Conference on Learning Theory. 940–947. 1 indexed citations
9.
Gamarnik, David, et al.. (2017). High Dimensional Regression with Binary Coefficients. Estimating Squared Error and a Phase Transtition.. Conference on Learning Theory. 948–953. 11 indexed citations
10.
Gamarnik, David & Quan Li. (2017). On the max‐cut of sparse random graphs. Random Structures and Algorithms. 52(2). 219–262. 9 indexed citations
11.
Anderson, Ross, Itai Ashlagi, David Gamarnik, & Yash Kanoria. (2014). A dynamic model of barter exchange. DSpace@MIT (Massachusetts Institute of Technology). 33 indexed citations
12.
Gamarnik, David, et al.. (2013). Strong spatial mixing of list coloring of graphs. Random Structures and Algorithms. 46(4). 599–613. 13 indexed citations
13.
Gamarnik, David & Alexander Stolyar. (2012). Multiclass multiserver queueing system in the Halfin–Whitt heavy traffic regime: asymptotics of the stationary distribution. Queueing Systems. 71(1-2). 25–51. 32 indexed citations
14.
Gamarnik, David, et al.. (2010). A deterministic approximation algorithm for computing the permanent of a 0,1 matrix. Journal of Computer and System Sciences. 76(8). 879–883. 5 indexed citations
15.
Gamarnik, David & Petar Momčilović. (2008). Steady-state analysis of a multiserver queue in the Halfin-Whitt regime. Advances in Applied Probability. 40(2). 548–577. 8 indexed citations
16.
Bandyopadhyay, Antar & David Gamarnik. (2006). Counting without sampling: new algorithms for enumeration problems using statistical physics. Symposium on Discrete Algorithms. 890–899. 22 indexed citations
17.
Gamarnik, David & Petar Momčilović. (2005). A Transposition Rule Analysis Based on a Particle Process. Journal of Applied Probability. 42(1). 235–246.
18.
Gamarnik, David & Assaf Zeevi. (2004). Validity of Heavy Traffic Steady-State Approximations in Open Queueing Networks. arXiv (Cornell University). 18 indexed citations
19.
Coppersmith, Don, David Gamarnik, & Maxim Sviridenko. (2002). The diameter of a long‐range percolation graph. Random Structures and Algorithms. 21(1). 1–13. 57 indexed citations
20.
Gamarnik, David. (2000). On deciding stability of scheduling policies in queueing systems. Symposium on Discrete Algorithms. 467–476. 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.

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