Madhur Tulsiani

805 citations
28 papers · 174 indexed · h-index 7
Topics
Complexity and Algorithms in Graphs (21 papers)Advanced Graph Theory Research (16 papers)Optimization and Search Problems (4 papers)
Journals
SIAM Journal on ComputingTheory of ComputingarXiv (Cornell University)

In The Last Decade

Madhur Tulsiani

25 papers receiving 160 citations

Peers

Madhur Tulsiani
Comparison fields: 5 of 31
  • Computational Theory and Mathematics 130
  • Artificial Intelligence 67
  • Computer Networks and Communications 58
  • Numerical Analysis 16
  • Computer Graphics and Computer-Aided Design 16
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Citations per field
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Euiwoong Lee · 1×
Citations per year

Countries citing papers authored by Madhur Tulsiani

Since Specialization
Citations

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

Fields of papers citing papers by Madhur Tulsiani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Madhur Tulsiani

This figure shows the co-authorship network connecting the top 25 collaborators of Madhur Tulsiani. A scholar is included among the top collaborators of Madhur Tulsiani 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 Madhur Tulsiani. Madhur Tulsiani 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
#WorkIndexed citations
1 1
2 4
3 8
4 2
5
Inapproximability of Matrix p→q Norms.
2
6
2
7 1
8
Multiplicative Approximations for Polynomial Optimization Over the Unit Sphere
4
9 5
10 8
11
$LS_+$ Lower Bounds from Pairwise Independence.
2
12
The Complexity of Somewhat Approximation Resistant Predicates.
0
13
27
14
Towards An Optimal Query Efficient PCP
0
15 36
16 7
17
Improved Pseudorandom Generators for Depth 2 Circuits.
2
18
On the Optimality of a Class of LP-based Algorithms
1
19
Non-uniform attacks against one-way functions and PRGs.
2
20 3

About Madhur Tulsiani

Madhur Tulsiani is a scholar working on Computational Mathematics, Computational Theory and Mathematics and Computer Graphics and Computer-Aided Design, having authored 28 papers that have together received 174 indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (21 papers), Advanced Graph Theory Research (16 papers) and Optimization and Search Problems (4 papers). The work is most often cited by research in Computational Theory and Mathematics (130 citations), Computational Mathematics (4 citations) and Computer Graphics and Computer-Aided Design (16 citations). Madhur Tulsiani has collaborated with scholars based in United States, Israel and Switzerland. Frequent co-authors include David Steurer, Prasad Raghavendra, Nisheeth K. Vishnoi, Subhash Khot, Siavosh Benabbas, Avner Magen, Sanjeev Arora, Konstantinos Georgiou, Alexandra Kolla and Luca Trevisan. Their work appears in journals such as SIAM Journal on Computing, Theory of Computing and arXiv (Cornell University).

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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