2026 C. Seshadhri: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	39	9887	9606	4157	3985	145	5086

C. Seshadhri publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where C. Seshadhri sits on this spectrum.

32 publications 991+

This scientist: 145 publications — 25th percentile

25% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

C. Seshadhri D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where C. Seshadhri sits on this spectrum.

30 D-Index 131+

This scientist: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

C. Seshadhri is a researcher affiliated with the University of California, Santa Cruz in the United States. Their work predominantly lies within the field of Computer Science, with a focus on computational theory, graph algorithms, and network analysis.

Their main subfields of study include:

Computational Theory and Mathematics
Statistical and Nonlinear Physics
Computer Networks and Communications
Artificial Intelligence
Molecular Biology

C. Seshadhri's research topics broadly cover areas such as complexity and algorithms in graphs, advanced graph theory research, and complex network analysis techniques. Additional topics include advanced graph neural networks, opinion dynamics and social influence, Markov chains and Monte Carlo methods, and graph theory applications.

They have contributed to several recent papers, among which are:

The impossibility of low-rank representations for triangle-rich complex networks, 2020, Proceedings of the National Academy of Sciences
On Approximating the Number of k-Cliques in Sublinear Time, 2020, SIAM Journal on Computing
Counting Subgraphs in Degenerate Graphs, 2022, Journal of the ACM
Link prediction using low-dimensional node embeddings: The measurement problem, 2024, Proceedings of the National Academy of Sciences
Finding Cliques in Social Networks: A New Distribution-Free Model, 2020, SIAM Journal on Computing

Frequent co-authors in their work include:

Andrew Stolman
Suman K. Bera
Akash Kumar
Talya Eden
Dana Ron

The researcher frequently publishes in venues such as:

arXiv (Cornell University)
SIAM Journal on Computing
Proceedings of the National Academy of Sciences
Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
Cambridge University Press eBooks

Best Publications

Community structure and scale-free collections of Erdős-Rényi graphs.

C. Seshadhri;Tamara G. Kolda;Ali Pinar

331
Citations
Vertex neighborhoods, low conductance cuts, and good seeds for local community methods

David F. Gleich;C. Seshadhri

247
Citations
A Scalable Generative Graph Model with Community Structure

Tamara G. Kolda;Ali Pinar;Todd D. Plantenga;C. Seshadhri

189
Citations
Efficient learning algorithms for changing environments

Elad Hazan;C. Seshadhri

178
Citations
ESCAPE: Efficiently Counting All 5-Vertex Subgraphs

Ali Pinar;C. Seshadhri;Vaidyanathan Vishal

175
Citations
A space efficient streaming algorithm for triangle counting using the birthday paradox

Madhav Jha;C. Seshadhri;Ali Pinar

161
Citations
Path Sampling: A Fast and Provable Method for Estimating 4-Vertex Subgraph Counts

Madhav Jha;C. Seshadhri;Ali Pinar

157
Citations
Finding the Hierarchy of Dense Subgraphs using Nucleus Decompositions

Ahmet Erdem Sariyuce;C. Seshadhri;Ali Pinar;Umit V. Catalyurek

155
Citations
Triadic Measures on Graphs: The Power of Wedge Sampling

C. Seshadhri;Ali Pinar;Tamara G. Kolda

145
Citations
FAST-PPR: scaling personalized pagerank estimation for large graphs

Peter A. Lofgren;Siddhartha Banerjee;Ashish Goel;C. Seshadhri

130
Citations
Approximately Counting Triangles in Sublinear Time

Talya Eden;Amit Levi;Dana Ron;C. Seshadhri

128
Citations
Blackbox Identity Testing for Bounded Top-Fanin Depth-3 Circuits: The Field Doesn't Matter

Nitin Saxena;C. Seshadhri

107
Citations
Optimal bounds for monotonicity and lipschitz testing over hypercubes and hypergrids

Deeparnab Chakrabarty;C. Seshadhri

101
Citations
Adaptive Algorithms for Online Decision Problems

Elad Hazan;C. Seshadhri

98
Citations
Counting Triangles in Massive Graphs with MapReduce

Tamara G. Kolda;Ali Pinar;Todd D. Plantenga;C. Seshadhri

95
Citations
An $o(n)$ Monotonicity Tester for Boolean Functions over the Hypercube

Deeparnab Chakrabarty;C. Seshadhri

95
Citations
Local algorithms for hierarchical dense subgraph discovery

Ahmet Erdem Sariyüce;C. Seshadhri;Ali Pinar

93
Citations
A Fast and Provable Method for Estimating Clique Counts Using Turán's Theorem

Shweta Jain;C. Seshadhri

91
Citations
Wedge sampling for computing clustering coefficients and triangle counts on large graphs

C. Seshadhri;Ali Pinar;Tamara G. Kolda

89
Citations
From sylvester-gallai configurations to rank bounds: Improved blackbox identity test for depth-3 circuits

Nitin Saxena;C. Seshadhri

75
Citations
A Fast and Provable Method for Estimating Clique Counts Using Tur'an's Theorem

Shweta Jain;C. Seshadhri

3
Citations

Frequent Co-Authors

Ali Pinar Sandia National Laboratories

Tamara G. Kolda Independent Scientist / Consultant, US

Dana Ron Tel Aviv University

Michael Saks Rutgers, The State University of New Jersey

Kenneth L. Clarkson IBM (United States)

Tim Roughgarden Columbia University

Satyen Kale Google (United States)

Bernard Chazelle Princeton University

Ümit V. Çatalyürek Georgia Institute of Technology

Elad Hazan Princeton University

External Links

Personal website of C. Seshadhri Google Scholar page

If you think any of the details on this page are incorrect, let us know.

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