World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
7757
World Ranking
9644
National Ranking
4085

Overview

Nagiza F. Samatova is affiliated with North Carolina State University in the United States. Their research spans the fields of Mathematics and Computer Science, with a focus on subfields such as Artificial Intelligence, Statistical and Nonlinear Physics, Applied Mathematics, Oceanography, and Mathematical Physics.

The primary topics addressed in their work include Nonlinear Waves and Solitons, Navier-Stokes equation solutions, Ocean Waves and Remote Sensing, Advanced Mathematical Physics Problems, Machine Learning and Data Classification, Imbalanced Data Classification Techniques, and Data Stream Mining Techniques.

Their recent publications include:

  • "Group classification of the two-dimensional shallow water equations with the beta-plane approximation of coriolis parameter in Lagrangian coordinates", 2020, Communications in Nonlinear Science and Numerical Simulation
  • "The one-dimensional Green-Naghdi equations with a time dependent bottom topography and their conservation laws", 2020, Physics of Fluids
  • "Predictive models with end user preference", 2021, Statistical Analysis and Data Mining The ASA Data Science Journal
  • "An analysis of junior rower performance and how it is affected by rower's features", 2022, Journal of Emerging Investigators

Frequent collaborators in their research include Sergey V. Meleshko, Е. И. Капцов, Yifan Zhao, Yang Xian, and Carolina Bolnykh.

The venues in which their work has appeared reflect their interdisciplinary interests and include Communications in Nonlinear Science and Numerical Simulation, Physics of Fluids, Statistical Analysis and Data Mining The ASA Data Science Journal, and Journal of Emerging Investigators.

Best Publications

  • Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data

    Anuj Karpatne;Gowtham Atluri;James H. Faghmous;Michael Steinbach

  • Detecting Differential and Correlated Protein Expression in Label-Free Shotgun Proteomics

    Bing Zhang;Nathan C. Verberkmoes;Michael A. Langston;Edward Uberbacher

  • Anomaly detection in dynamic networks: a survey

    Stephen Ranshous;Stephen Ranshous;Shitian Shen;Shitian Shen;Danai Koutra;Steve Harenberg;Steve Harenberg

  • Gene network shaping of inherent noise spectra

    D. Austin;D. Austin;M. Allen;J. Mccollum;R. Dar

  • Community detection in large‐scale networks: a survey and empirical evaluation

    Steve Harenberg;Steve Harenberg;Gonzalo Bello;Gonzalo Bello;L. Gjeltema;L. Gjeltema;Stephen Ranshous;Stephen Ranshous

  • Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks

    Qing Liu;Jeremy Logan;Yuan Tian;Hasan Abbasi

  • The sorting direct method for stochastic simulation of biochemical systems with varying reaction execution behavior

    James M. McCollum;Gregory D. Peterson;Chris D. Cox;Michael L. Simpson

  • Compressing the incompressible with ISABELA: in-situ reduction of spatio-temporal data

    Sriram Lakshminarasimhan;Neil Shah;Stephane Ethier;Scott Klasky

  • A scalable, parallel algorithm for maximal clique enumeration

    Matthew C. Schmidt;Nagiza F. Samatova;Kevin Thomas;Byung-Hoon Park

  • From pull-down data to protein interaction networks and complexes with biological relevance

    Bing Zhang;Byung-Hoon Park;Tatiana Karpinets;Nagiza F. Samatova

  • Community-based anomaly detection in evolutionary networks

    Zhengzhang Chen;William Hendrix;Nagiza F. Samatova

  • Method for gathering and summarizing internet information

    Thomas E. Potok;Mark Thomas Elmore;Joel Wesley Reed;Jim N. Treadwell

  • Improved genome annotation for Zymomonas mobilis.

    Shihui Yang;Katherine M Pappas;Loren J Hauser;Miriam L Land

  • ProRata: A quantitative proteomics program for accurate protein abundance ratio estimation with confidence interval evaluation.

    Chongle Pan;Guruprasad H Kora;W Hayes McDonald;Dave L Tabb

  • ISABELA for effective in situ compression of scientific data

    Sriram Lakshminarasimhan;Sriram Lakshminarasimhan;Neil Shah;Stéphane Ethier;Seung-Hoe Ku

  • Efficient data access for parallel BLAST

    Heshan Lin;Xiaosong Ma;P. Chandramohan;A. Geist

  • Genome-Scale Computational Approaches to Memory-Intensive Applications in Systems Biology

    Yun Zhang;Faisal N. Abu-Khzam;Nicole E. Baldwin;Elissa J. Chesler

  • Learning Entity Type Embeddings for Knowledge Graph Completion

    Changsung Moon;Paul Jones;Nagiza F. Samatova

  • ISABELA-QA: query-driven analytics with ISABELA-compressed extreme-scale scientific data

    Sriram Lakshminarasimhan;John Jenkins;Isha Arkatkar;Zhenhuan Gong

  • RACHET: An Efficient Cover-Based Merging of Clustering Hierarchies from Distributed Datasets

    Nagiza F. Samatova;George Ostrouchov;Al Geist;Anatoli V. Melechko

  • An Introduction to Graph Theory

    Nagiza F. Samatova;William Hendrix;John Jenkins;Kanchana Padmanabhan

  • Theory-guided Data Science: A New Paradigm for Scientific Discovery.

    Anuj Karpatne;Gowtham Atluri;James H. Faghmous;Michael S. Steinbach

  • Scientific Data Analysis.

    Chandrika Kamath;Nikil Wale;George Karypis;Gaurav Pandey

Frequent Co-Authors

Scott Klasky
Scott Klasky Oak Ridge National Laboratory
Vipin Kumar
Vipin Kumar University of Minnesota
Robert Ross
Robert Ross Argonne National Laboratory
Alok Choudhary
Alok Choudhary Northwestern University
Robert L. Hettich
Robert L. Hettich Oak Ridge National Laboratory
Michael L. Simpson
Michael L. Simpson University of Tennessee at Knoxville
James R. Mihelcic
James R. Mihelcic University of South Florida
Kesheng Wu
Kesheng Wu Lawrence Berkeley National Laboratory
Dale A. Pelletier
Dale A. Pelletier Oak Ridge National Laboratory
Michael A. Langston
Michael A. Langston University of Tennessee at Knoxville

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