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Computer Science

D-Index
39
Citations
5086
World Ranking
9888
National Ranking
4157

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

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

    David F. Gleich;C. Seshadhri

  • A Scalable Generative Graph Model with Community Structure

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

  • Efficient learning algorithms for changing environments

    Elad Hazan;C. Seshadhri

  • ESCAPE: Efficiently Counting All 5-Vertex Subgraphs

    Ali Pinar;C. Seshadhri;Vaidyanathan Vishal

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

    Madhav Jha;C. Seshadhri;Ali Pinar

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

    Madhav Jha;C. Seshadhri;Ali Pinar

  • Finding the Hierarchy of Dense Subgraphs using Nucleus Decompositions

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

  • Triadic Measures on Graphs: The Power of Wedge Sampling

    C. Seshadhri;Ali Pinar;Tamara G. Kolda

  • FAST-PPR: scaling personalized pagerank estimation for large graphs

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

  • Approximately Counting Triangles in Sublinear Time

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

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

    Nitin Saxena;C. Seshadhri

  • Optimal bounds for monotonicity and lipschitz testing over hypercubes and hypergrids

    Deeparnab Chakrabarty;C. Seshadhri

  • Adaptive Algorithms for Online Decision Problems

    Elad Hazan;C. Seshadhri

  • Counting Triangles in Massive Graphs with MapReduce

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

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

    Deeparnab Chakrabarty;C. Seshadhri

  • Local algorithms for hierarchical dense subgraph discovery

    Ahmet Erdem Sariyüce;C. Seshadhri;Ali Pinar

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

    Shweta Jain;C. Seshadhri

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

    C. Seshadhri;Ali Pinar;Tamara G. Kolda

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

    Nitin Saxena;C. Seshadhri

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

    Shweta Jain;C. Seshadhri

Frequent Co-Authors

Ali Pinar
Ali Pinar Sandia National Laboratories
Tamara G. Kolda
Tamara G. Kolda Independent Scientist / Consultant, US
Dana Ron
Dana Ron Tel Aviv University
Michael Saks
Michael Saks Rutgers, The State University of New Jersey
Kenneth L. Clarkson
Kenneth L. Clarkson IBM (United States)
Tim Roughgarden
Tim Roughgarden Columbia University
Satyen Kale
Satyen Kale Google (United States)
Bernard Chazelle
Bernard Chazelle Princeton University
Ümit V. Çatalyürek
Ümit V. Çatalyürek Georgia Institute of Technology
Elad Hazan
Elad Hazan Princeton University

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