World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
14748
World Ranking
5769
National Ranking
2623

Research.com Recognitions

  • 2013 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

Ananth Grama is affiliated with Purdue University West Lafayette in the United States and has a research profile that spans computer science and medicine, with a significant number of publications in both areas. Their work includes studies across artificial intelligence, molecular biology, management science and operations research, computer networks and communications, and cognitive neuroscience.

Grama's primary fields of study are Computer Science, with 40 publications, and Medicine, with 22 publications. Their research delves into subfields such as:

  • Artificial Intelligence
  • Molecular Biology
  • Management Science and Operations Research
  • Computer Networks and Communications
  • Cognitive Neuroscience

The main topics covered by Grama's research include:

  • Advanced Bandit Algorithms Research
  • Liver Disease and Transplantation
  • Acute Kidney Injury Research
  • Bioinformatics and Genomic Networks
  • Neural Networks and Applications
  • Machine Learning and Algorithms
  • Advanced Graph Neural Networks

Their recent publications illustrate a blend of medical and computational studies. Key papers include:

  • "Acute kidney disease is common and associated with poor outcomes in patients with cirrhosis and acute kidney injury" (2022), Journal of Hepatology
  • "Cybernetic modeling of biological processes in mammalian systems" (2020), Current Opinion in Chemical Engineering
  • "Practice patterns and outcomes associated with intravenous albumin in patients with cirrhosis and acute kidney injury" (2021), Liver International
  • "Constructing Compact Signatures for Individual Fingerprinting of Brain Connectomes" (2021), Frontiers in Neuroscience
  • "Toward Physically Realizable Quantum Neural Networks" (2022), Proceedings of the AAAI Conference on Artificial Intelligence

Frequent coauthors in their work include Wojciech Szpankowski, Mohammad Adibuzzaman, Mohsen Heidari, Vikram Ravindra, and Changlong Wu.

Grama has published extensively in venues such as:

  • arXiv (Cornell University)
  • PLOS Digital Health
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of Hepatology
  • Current Opinion in Chemical Engineering

Award recognition includes being named a Fellow of the American Association for the Advancement of Science (AAAS) in 2013.

Best Publications

  • Introduction to parallel computing: design and analysis of algorithms

    Vipin Kumar;Ananth Grama;Anshul Gupta;George Karypis

  • The ReaxFF reactive force-field: development, applications and future directions

    Thomas P. Senftle;Sungwook Hong;Mahbubul Islam;Sudhir B. Kylasa

  • Trends in big data analytics

    Karthik Kambatla;Giorgios Kollias;Vipin Kumar;Ananth Grama

  • Parallel reactive molecular dynamics: Numerical methods and algorithmic techniques

    H. M. Aktulga;J. C. Fogarty;S. A. Pandit;A. Y. Grama

  • Isoefficiency: measuring the scalability of parallel algorithms and architectures

    Ananth Y. Grama;Anshul Gupta;Vipin Kumar

  • Pairwise alignment of protein interaction networks.

    Mehmet Koyutürk;Yohan Kim;Umut Topkara;Shankar Subramaniam

  • Scalable Load Balancing Techniques for Parallel Computers

    V. Kumar;A.Y. Grama;N.R. Vempaty

  • An efficient algorithm for detecting frequent subgraphs in biological networks

    Mehmet Koyutürk;Ananth Grama;Wojciech Szpankowski

  • Privacy risks in recommender systems

    N. Ramakrishnan;B.J. Keller;B.J. Mirza;A.Y. Grama

  • Redundancy and coverage detection in sensor networks

    Bogdan Cărbunar;Ananth Grama;Jan Vitek;Octavian Cărbunar

  • The MG-RAST Metagenomics Database and Portal in 2015

    Andreas Wilke;Jared Bischof;Jared Bischof;Wolfgang Gerlach;Wolfgang Gerlach;Elizabeth M. Glass;Elizabeth M. Glass

  • MODE: automated neural network model debugging via state differential analysis and input selection

    Shiqing Ma;Yingqi Liu;Wen-Chuan Lee;Xiangyu Zhang

  • A secure protocol for computing dot-products in clustered and distributed environments

    I. Ioannidis;A. Grama;M. Atallah

  • An efficient protocol for Yao's millionaires' problem

    I. Ioannidis;A. Grama

  • Redundant reader elimination in RFID systems

    B. Carbunar;M.K. Ramanathan;M. Koyuturk;C. Hoffmann

  • Data mining: from serendipity to science

    N. Ramakrishnan;A.Y. Grama

  • MG-RAST version 4-lessons learned from a decade of low-budget ultra-high-throughput metagenome analysis.

    Folker Meyer;Saurabh Bagchi;Somali Chaterji;Wolfgang Gerlach

  • Path-Sensitive Inference of Function Precedence Protocols

    Murali Krishna Ramanathan;Ananth Grama;Suresh Jagannathan

  • Static specification inference using predicate mining

    Murali Krishna Ramanathan;Ananth Grama;Suresh Jagannathan

  • State of the art in parallel search techniques for discrete optimization problems

    A. Grama;V. Kumar

Frequent Co-Authors

Suresh Jagannathan
Suresh Jagannathan Purdue University West Lafayette
Wojciech Szpankowski
Wojciech Szpankowski Purdue University West Lafayette
Vipin Kumar
Vipin Kumar University of Minnesota
Ahmed Sameh
Ahmed Sameh Purdue University West Lafayette
Shankar Subramaniam
Shankar Subramaniam University of California, San Diego
Naren Ramakrishnan
Naren Ramakrishnan Virginia Tech
David F. Gleich
David F. Gleich Purdue University West Lafayette
George Karypis
George Karypis University of Minnesota
Michael W. Mahoney
Michael W. Mahoney University of California, Berkeley
Saurabh Bagchi
Saurabh Bagchi Purdue University West Lafayette

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