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Computer Science

D-Index
35
Citations
8345
World Ranking
11471
National Ranking
4711

Overview

Naeem Seliya is affiliated with the University of Wisconsin-Eau Claire in the United States. Their research predominantly lies within the domain of computer science, with a primary focus on artificial intelligence, information systems, and signal processing. The scientist has contributed extensively to subfields such as computer networks and communications as well as human-computer interaction.

Their work covers a range of main topics, including user authentication and security systems, advanced malware detection techniques, and IoT and edge/fog computing. Additional areas of interest encompass anomaly detection techniques and applications, context-aware activity recognition systems, biometric identification and security, and network security and intrusion detection.

Frequently collaborating with other researchers, Naeem Seliya's notable coauthors include Rushit Dave, Nyle Siddiqui, Mounika Vanamala, Jacob Mallet, and Taghi M. Khoshgoftaar. These collaborations have been spread across multiple projects and publications.

Seliya's research outputs have appeared in various publication venues, with multiple papers published in the following outlets:

  • arXiv (Cornell University)
  • Journal Of Big Data
  • Journal of Computer Sciences and Applications
  • 2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML)
  • 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)

Among their recent papers are:

  • A literature review on one-class classification and its potential applications in big data (2021, Journal Of Big Data)
  • Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detection (2021, Information)
  • Machine and Deep Learning Applications to Mouse Dynamics for Continuous User Authentication (2022, Machine Learning and Knowledge Extraction)
  • A Modern Analysis of Aging Machine Learning Based IoT Cybersecurity Methods (2021, Journal of Computer Sciences and Applications)
  • The Benefits of Edge Computing in Healthcare, Smart Cities, and IoT (2021, Journal of Computer Sciences and Applications)

Best Publications

  • Deep learning applications and challenges in big data analytics

    Maryam M Najafabadi;Flavio Villanustre;Taghi M Khoshgoftaar;Naeem Seliya

  • A survey on addressing high-class imbalance in big data

    Joffrey L. Leevy;Taghi M. Khoshgoftaar;Richard A. Bauder;Naeem Seliya

  • Choosing software metrics for defect prediction: an investigation on feature selection techniques

    Kehan Gao;Taghi M. Khoshgoftaar;Huanjing Wang;Naeem Seliya

  • A Study on the Relationships of Classifier Performance Metrics

    Naeem Seliya;Taghi M. Khoshgoftaar;Jason Van Hulse

  • Comparative Assessment of Software Quality Classification Techniques: An Empirical Case Study

    Taghi M. Khoshgoftaar;Naeem Seliya

  • Analyzing software measurement data with clustering techniques

    S. Zhong;T.M. Khoshgoftaar;N. Seliya

  • Tree-based software quality estimation models for fault prediction

    T.M. Khoshgoftaar;N. Seliya

  • Attribute Selection and Imbalanced Data: Problems in Software Defect Prediction

    Taghi M. Khoshgoftaar;Kehan Gao;Naeem Seliya

  • Fault Prediction Modeling for Software Quality Estimation: Comparing Commonly Used Techniques

    Taghi M. Khoshgoftaar;Naeem Seliya

  • Evolutionary Optimization of Software Quality Modeling with Multiple Repositories

    Yi Liu;Taghi M Khoshgoftaar;Naeem Seliya

  • A literature review on one-class classification and its potential applications in big data

    Naeem Seliya;Azadeh Abdollah Zadeh;Taghi M. Khoshgoftaar

  • CLUSTERING-BASED NETWORK INTRUSION DETECTION

    Shi Zhong;Taghi M. Khoshgoftaar;Naeem Seliya

  • Software Quality Classification Modeling Using the SPRINT Decision Tree Algorithm

    Taghi M. Khoshgoftaar;Naeem Seliya

  • Unsupervised learning for expert-based software quality estimation

    Shi Zhong;T.M. Khoshgoftaar;N. Seliya

  • A survey on the state of healthcare upcoding fraud analysis and detection

    Richard Bauder;Taghi M. Khoshgoftaar;Naeem Seliya

  • An empirical study of predicting software faults with case-based reasoning

    Taghi M. Khoshgoftaar;Naeem Seliya;Nandini Sundaresh

  • Analogy-Based Practical Classification Rules for Software Quality Estimation

    Taghi M. Khoshgoftaar;Naeem Seliya

  • Software Quality Analysis of Unlabeled Program Modules With Semisupervised Clustering

    N. Seliya;T.M. Khoshgoftaar

  • Software quality estimation with limited fault data: a semi-supervised learning perspective

    Naeem Seliya;Taghi M. Khoshgoftaar

  • Machine Learning for Detecting Brute Force Attacks at the Network Level

    Maryam M. Najafabadi;Taghi M. Khoshgoftaar;Clifford Kemp;Naeem Seliya

Frequent Co-Authors

Taghi M. Khoshgoftaar
Taghi M. Khoshgoftaar Florida Atlantic University
Bojan Cukic
Bojan Cukic University of North Carolina at Charlotte
Mayuram S. Krishnan
Mayuram S. Krishnan University of Michigan–Ann Arbor

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