World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
95
Citations
64130
World Ranking
452
National Ranking
248

Overview

Taghi M. Khoshgoftaar is a researcher affiliated with Florida Atlantic University in the United States. Their work primarily belongs to the field of Computer Science, with a strong focus on several subfields including Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems, and Computer Vision and Pattern Recognition.

Their research covers multiple topics such as Imbalanced Data Classification Techniques, Machine Learning and Data Classification, Anomaly Detection Techniques and Applications, Network Security and Intrusion Detection, Electricity Theft Detection Techniques, Advanced Malware Detection Techniques, and Internet Traffic Analysis and Secure E-voting.

They have published extensively in several venues, notably the Journal Of Big Data, where they have 41 publications. Other frequent publication venues include SN Computer Science, International Journal of Internet of Things and Cyber-Assurance, the 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), and the International Journal of Reliability Quality and Safety Engineering.

Among their recent published papers are:

  • Feature selection strategies: a comparative analysis of SHAP-value and importance-based methods (2024) in Journal Of Big Data
  • Text Data Augmentation for Deep Learning (2021) in Journal Of Big Data
  • Deep Learning applications for COVID-19 (2021) in Journal Of Big Data
  • CatBoost for big data: an interdisciplinary review (2020) in Journal Of Big Data
  • Survey on categorical data for neural networks (2020) in Journal Of Big Data

They have also contributed to book publications, including a work published by Springer Nature titled Deep Learning Applications, Volume 2 in 2020.

Frequent coauthors of Taghi M. Khoshgoftaar include:

  • Joffrey L. Leevy
  • John Hancock
  • Justin Johnson
  • Connor Shorten
  • John M. Hancock

Best Publications

  • A survey on Image Data Augmentation for Deep Learning

    Connor Shorten;Taghi M. Khoshgoftaar

  • A survey of transfer learning

    Karl R. Weiss;Taghi M. Khoshgoftaar;Dingding Wang

  • A survey of collaborative filtering techniques

    Xiaoyuan Su;Taghi M. Khoshgoftaar

  • Deep learning applications and challenges in big data analytics

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

  • Survey on deep learning with class imbalance

    Justin M. Johnson;Taghi M. Khoshgoftaar

  • RUSBoost: A Hybrid Approach to Alleviating Class Imbalance

    C. Seiffert;T.M. Khoshgoftaar;J. Van Hulse;A. Napolitano

  • CatBoost for big data: an interdisciplinary review

    John T. Hancock;Taghi M. Khoshgoftaar

  • Text Data Augmentation for Deep Learning.

    Connor Shorten;Taghi M. Khoshgoftaar;Borko Furht

  • Experimental perspectives on learning from imbalanced data

    Jason Van Hulse;Taghi M. Khoshgoftaar;Amri Napolitano

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

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

  • The detection of fault-prone programs

    J.C. Munson;T.M. Khoshgoftaar

  • Survey on categorical data for neural networks

    John T. Hancock;Taghi M. Khoshgoftaar

  • A survey of open source tools for machine learning with big data in the Hadoop ecosystem

    Sara Landset;Taghi M. Khoshgoftaar;Aaron N. Richter;Tawfiq Hasanin

  • Survey of review spam detection using machine learning techniques

    Michael Crawford;Taghi M. Khoshgoftaar;Joseph D. Prusa;Aaron N. Richter

  • Intrusion detection and Big Heterogeneous Data: a Survey

    Richard Zuech;Taghi M Khoshgoftaar;Randall Wald

  • A review of data mining using big data in health informatics

    Matthew Herland;Taghi M Khoshgoftaar;Randall Wald

  • A survey on heterogeneous transfer learning

    Oscar Day;Taghi M. Khoshgoftaar

  • An Empirical Study of Learning from Imbalanced Data Using Random Forest

    T.M. Khoshgoftaar;M. Golawala;J. Van Hulse

  • Big Data: Deep Learning for financial sentiment analysis

    Sahar Sohangir;Dingding Wang;Anna Pomeranets;Taghi M. Khoshgoftaar

  • Feature selection strategies: a comparative analysis of SHAP-value and importance-based methods

    Unknown

  • Predicting software development errors using software complexity metrics

    T.M. Khoshgoftaar;J.C. Munson

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

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

  • Comparing Boosting and Bagging Techniques With Noisy and Imbalanced Data

    T M Khoshgoftaar;J Van Hulse;A Napolitano

Frequent Co-Authors

Naeem Seliya
Naeem Seliya University of Wisconsin–Eau Claire
Edward B. Allen
Edward B. Allen Mississippi State University
Alain Abran
Alain Abran École de Technologie Supérieure
Borko Furht
Borko Furht Florida Atlantic University
Ali Idri
Ali Idri Mohammed V University
Mayuram S. Krishnan
Mayuram S. Krishnan University of Michigan–Ann Arbor

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online degrees is a flexible and cost-effective way to start or advance your computer science career in the USA. Many students choose to pursue an associates degrees online to gain foundational skills and enter the tech workforce quickly. These programs can be a stepping stone to higher education or directly into entry-level IT roles.

For those seeking to boost their qualifications rapidly, pursuing the shortest online masters degree can help you earn a credential in less time, balancing speed with quality learning. It’s also important to consider what programs provide the best return on investment: learn which are the best masters degree to get for long-term career growth and high-demand roles.

If affordability is a key concern, plenty of reputable colleges offer quality education at reduced rates. Discover some of the cheapest online degrees to minimize financial stress while building your future. With so many options available, choosing the right online pathway can set the stage for a successful and fulfilling tech career.

Best Scientists Citing Taghi M. Khoshgoftaar

Trending Scientists

Recently Published Articles