World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
7017
World Ranking
7291
National Ranking
3180

Research.com Recognitions

  • 1989 - IEEE Fellow For contributions to theory of multivariable networks with applications to two-dimensional digital filters.

Overview

Vijaya Ramachandran is affiliated with The University of Texas at Austin in the United States. Their research contributions span multiple fields and subfields within computer science and electrical engineering.

Their main field of study is Computer Science, with publications covering various subfields such as:

  • Electrical and Electronic Engineering
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing

Ramachandran's work addresses a range of topics, including:

  • Advanced Optical Network Technologies
  • Advanced Graph Theory Research
  • Interconnection Networks and Systems
  • Parallel Computing and Optimization Techniques
  • Data Management and Algorithms

Their recent papers include:

  • Scalable Data Structures (Dagstuhl Seminar 21071), 2021, published at Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Distributed Distance Sensitivity Oracles, 2024, published on arXiv (Cornell University)

Frequent co-authors in their research collaborations are:

  • Vignesh Manoharan
  • Gerth Stølting Brodal
  • John Iacono
  • Markus E. Nebel

The primary publication venues for their work include:

  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • arXiv (Cornell University)

In recognition of their contributions to the field, Vijaya Ramachandran was named an IEEE Fellow in 1989, cited for work on the theory of multivariable networks with applications to two-dimensional digital filters.

Best Publications

  • Parallel algorithms for shared-memory machines

    Richard M. Karp;Vijaya Ramachandran

  • An optimal minimum spanning tree algorithm

    Seth Pettie;Vijaya Ramachandran

  • The Queue-Read Queue-Write PRAM Model: Accounting for Contention in Parallel Algorithms

    Phillip B. Gibbons;Yossi Matias;Vijaya Ramachandran

  • Flexible Hardware Acceleration for Instruction-Grain Program Monitoring

    Shimin Chen;Michael Kozuch;Theodoros Strigkos;Babak Falsafi

  • Provably good multicore cache performance for divide-and-conquer algorithms

    Guy E. Blelloch;Rezaul A. Chowdhury;Phillip B. Gibbons;Vijaya Ramachandran

  • Efficient parallel evaluation of straight-line code and arithmetic circuits

    Gary L. Miller;Vijaya Ramachandran;Erich Kaltofen

  • Can a Shared-Memory Model Serve as a Bridging Model for Parallel Computation?

    Phillip B. Gibbons;Yossi Matias;Vijaya Ramachandran

  • Design principles of policy languages for path vector protocols

    Timothy G. Griffin;Aaron D. Jaggard;Vijay Ramachandran

  • Oracles for Distances Avoiding a Failed Node or Link

    Camil Demetrescu;Mikkel Thorup;Rezaul Alam Chowdhury;Vijaya Ramachandran

  • An optimal parallel algorithm for formula evaluation

    S. Buss;S. Cook;A. Gupta;V. Ramachandran

  • Oblivious algorithms for multicores and networks of processors

    Rezaul Alam Chowdhury;Vijaya Ramachandran;Francesco Silvestri;Brandon Blakeley

  • Oblivious algorithms for multicores and network of processors

    Rezaul Alam Chowdhury;Francesco Silvestri;Brandon Blakeley;Vijaya Ramachandran

  • Finding a smallest augmentation to biconnect a graph

    Tsan-Sheng Hsu;Vijaya Ramachandran

  • Cache-efficient dynamic programming algorithms for multicores

    Rezaul Alam Chowdhury;Vijaya Ramachandran

  • A linear time algorithm for triconnectivity augmentation

    T.-S. Hsu;V. Ramachandran

  • Cache-oblivious dynamic programming

    Rezaul Alam Chowdhury;Vijaya Ramachandran

  • Can shared-memory model serve as a bridging model for parallel computation?

    Phillip B. Gibbons;Yossi Matias;Vijaya Ramachandran

  • The k-orientability thresholds for Gn, p

    Daniel Fernholz;Vijaya Ramachandran

  • The QRQW PRAM: accounting for contention in parallel algorithms

    Phillip B. Gibbons;Yossi Matias;Vijaya Ramachandran

  • The diameter of sparse random graphs

    Daniel Fernholz;Vijaya Ramachandran

  • Parallelizing dynamic information flow tracking

    Olatunji Ruwase;Phillip B. Gibbons;Todd C. Mowry;Vijaya Ramachandran

  • A Shortest Path Algorithm for Real-Weighted Undirected Graphs

    Seth Pettie;Vijaya Ramachandran

Frequent Co-Authors

Phillip B. Gibbons
Phillip B. Gibbons Carnegie Mellon University
Seth Pettie
Seth Pettie University of Michigan–Ann Arbor
Yossi Matias
Yossi Matias Google (United States)
Richard Cole
Richard Cole New York University
Tandy Warnow
Tandy Warnow University of Illinois at Urbana-Champaign
Gary L. Miller
Gary L. Miller Carnegie Mellon University
Robert E. Tarjan
Robert E. Tarjan Princeton University
Richard M. Karp
Richard M. Karp University of California, Berkeley
Michael Kozuch
Michael Kozuch Intel (United States)
Todd C. Mowry
Todd C. Mowry Carnegie Mellon University

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