World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
9920
World Ranking
4378
National Ranking
2041

Overview

J. Ramanujam is affiliated with Louisiana State University in the United States. Their research spans multiple fields, notably Computer Science and Biochemistry, Genetics, and Molecular Biology. The focus of their scholarly work includes several key subfields such as Molecular Biology, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Organic Chemistry, and Artificial Intelligence.

Their main research topics cover a range of areas including Computational Drug Discovery Methods, Bioinformatics and Genomic Networks, Protein Structure and Dynamics, Click Chemistry and Applications, Machine Learning in Bioinformatics, Gene Expression and Cancer Classification, and Human Pose and Action Recognition.

Ramanujam has authored multiple research papers published in diverse venues. Notable recent publications include:

  • "Strengthening spatial reasoning: elucidating the attentional and neural mechanisms associated with mental rotation skill development," 2020, Cognitive Research Principles and Implications
  • "Unlocking the Potential of Kinase Targets in Cancer: Insights from CancerOmicsNet, an AI-Driven Approach to Drug Response Prediction in Cancer," 2023, Cancers
  • "GraphDTI: A robust deep learning predictor of drug-target interactions from multiple heterogeneous data," 2021, Journal of Cheminformatics
  • "CancerOmicsNet: a multi-omics network-based approach to anti-cancer drug profiling," 2022, Oncotarget
  • "GraphSite: Ligand Binding Site Classification with Deep Graph Learning," 2022, Biomolecules

Frequent publication venues for Ramanujam include Biomolecules, bioRxiv (Cold Spring Harbor Laboratory), arXiv (Cornell University), Cancers, and Cognitive Research Principles and Implications. This reflects active engagement in both preprint and peer-reviewed platforms across biology and computer science disciplines.

Collaboration has been a significant aspect of Ramanujam's research, with several frequent coauthors contributing to their body of work. Frequent collaborators include Michał Bryliński, Manali Singha, Limeng Pu, Gopal Srivastava, and Wentao Shi, each involved in multiple joint publications.

Best Publications

  • A practical automatic polyhedral parallelizer and locality optimizer

    Uday Bondhugula;Albert Hartono;J. Ramanujam;P. Sadayappan

  • Dynamic management of scratch-pad memory space

    M. Kandemir;J. Ramanujam;J. Irwin;N. Vijaykrishnan

  • Automatic transformations for communication-minimized parallelization and locality optimization in the polyhedral model

    Uday Bondhugula;Muthu Baskaran;Sriram Krishnamoorthy;J. Ramanujam

  • Automatic C-to-CUDA code generation for affine programs

    Muthu Manikandan Baskaran;J. Ramanujam;P. Sadayappan

  • A compiler framework for optimization of affine loop nests for gpgpus

    Muthu Manikandan Baskaran;Uday Bondhugula;Sriram Krishnamoorthy;J. Ramanujam

  • Effective automatic parallelization of stencil computations

    Sriram Krishnamoorthy;Muthu Baskaran;Uday Bondhugula;J. Ramanujam

  • Synthesis of High-Performance Parallel Programs for a Class of ab Initio Quantum Chemistry Models

    G. Baumgartner;A. Auer;D.E. Bernholdt;A. Bibireata

  • Compile-time techniques for data distribution in distributed memory machines

    J. Ramanujam;P. Sadayappan

  • Tiling multidimensional iteration spaces for multicomputers

    J. Ramanujam;P. Sadayappan

  • Automatic code generation for many-body electronic structure methods: the tensor contraction engine‡‡

    Alexander A. Auer;Gerald Baumgartner;David E. Bernholdt;Alina Bibireata

  • A stencil compiler for short-vector SIMD architectures

    Tom Henretty;Richard Veras;Franz Franchetti;Louis-Noël Pouchet

  • Data layout transformation for stencil computations on short-vector SIMD architectures

    Tom Henretty;Kevin Stock;Louis-Noël Pouchet;Franz Franchetti

  • Loop transformations: convexity, pruning and optimization

    Louis-Noël Pouchet;Uday Bondhugula;Cédric Bastoul;Albert Cohen

  • Cluster partitioning approaches to mapping parallel programs onto a hypercube

    P. Sadayappan;Fikret Erçal;J. Ramanujam

  • Automatic data movement and computation mapping for multi-level parallel architectures with explicitly managed memories

    Muthu Manikandan Baskaran;Uday Bondhugula;Sriram Krishnamoorthy;J. Ramanujam

  • PLuTo: A Practical and Fully Automatic Polyhedral Program Optimization System

    Uday Bondhugula;J. Ramanujam;P. Sadayappan

  • Improving cache locality by a combination of loop and data transformations

    M. Kandemir;J. Ramanujam;A. Choudhary

  • Improving locality using loop and data transformations in an integrated framework

    M. Kandemir;A. Choudhary;J. Ramanujam;P. Banerjee

  • Exploiting shared scratch pad memory space in embedded multiprocessor systems

    Mahmut Kandemir;J. Ramanujam;A. Choudhary

  • Parametric multi-level tiling of imperfectly nested loops

    Albert Hartono;Muthu Manikandan Baskaran;Cédric Bastoul;Albert Cohen

  • Task allocation onto a hypercube by recursive mincut bipartitioning

    F. Ercal;J. Ramanujam;P. Sadayappan

  • Compilers and Operating Systems for Low Power

    Luca Benini;Mahmut Kandemir;J. Ramanujam

Frequent Co-Authors

P. Sadayappan
P. Sadayappan University of Utah
Mahmut Kandemir
Mahmut Kandemir Pennsylvania State University
Alok Choudhary
Alok Choudhary Northwestern University
Louis-Noël Pouchet
Louis-Noël Pouchet Colorado State University
Sriram Krishnamoorthy
Sriram Krishnamoorthy University of California, Santa Barbara
Prithviraj Banerjee
Prithviraj Banerjee Ansys (United States)
Atanas Rountev
Atanas Rountev The Ohio State University
Albert Cohen
Albert Cohen Google (United States)
Eduard Ayguadé
Eduard Ayguadé Barcelona Supercomputing Center
Mary Jane Irwin
Mary Jane Irwin Pennsylvania State University

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