David Gamarnik

3.6k citations
104 papers · 1.5k indexed · h-index 23

David Gamarnik

95 papers receiving 1.4k citations

Peers

David Gamarnik
Comparison fields: 5 of 93
  • Statistics and Probability 322
  • Management Information Systems 337
  • Discrete Mathematics and Combinatorics 113
  • Computational Theory and Mathematics 421
  • Computer Networks and Communications 496
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Citations per year

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

The 25 scholars most cited alongside David Gamarnik, 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 David Gamarnik Line = papers co-authored together David Gamarnik links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20240
3 20242
4 20221
5
High Dimensional Linear Regression using Lattice Basis Reduction
20180
6 20186
7 201755
8
Matrix Completion from $O(n)$ Samples in Linear Time.
20171
9
High Dimensional Regression with Binary Coefficients. Estimating Squared Error and a Phase Transtition.
201711
10 20179
11 201433
12 201313
13 201232
14 20105
15 20088
16 200622
17 20050
18
Validity of Heavy Traffic Steady-State Approximations in Open Queueing Networks
200418
19 200257
20 20005

About David Gamarnik

David Gamarnik is a scholar working on Discrete Mathematics and Combinatorics, Statistics and Probability, Management Information Systems, Computational Theory and Mathematics and Mathematical Physics, having authored 104 papers that have together received 1.5k indexed citations. Recurring topics across this work include Advanced Queuing Theory Analysis (27 papers), Markov Chains and Monte Carlo Methods (26 papers), Complexity and Algorithms in Graphs (20 papers), Stochastic processes and statistical mechanics (17 papers), Advanced Wireless Network Optimization (16 papers), Advanced Graph Theory Research (16 papers), Limits and Structures in Graph Theory (13 papers) and Machine Learning and Algorithms (12 papers). The work is most often cited by research in Statistics and Probability (322 citations), Management Information Systems (337 citations), Discrete Mathematics and Combinatorics (113 citations), Computational Theory and Mathematics (421 citations) and Computer Networks and Communications (496 citations). David Gamarnik has collaborated with scholars based in United States, Canada and United Kingdom. Frequent 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. Their work appears in journals such as Random Structures and Algorithms, The Annals of Applied Probability, Queueing Systems, Mathematics of Operations Research and Operations Research.

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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