Taghi M. Khoshgoftaar

Papers

Total Citations

359

H-Index

About

Taghi M. Khoshgoftaar is a leading authority in data mining, machine learning, and big data analytics, with a career-long focus on developing robust predictive models for high-stakes domains. His most impactful work includes a landmark 2021 survey on deep learning applications for COVID-19, which has garnered over 350 citations. This comprehensive review systematically examines how deep learning techniques—spanning natural language processing, computer vision, life sciences, and epidemiology—were mobilized to combat the pandemic, offering critical directions for future research. Beyond this, Khoshgoftaar has made foundational contributions to software engineering, particularly in software quality estimation and fault prediction, where his methods for handling class imbalance and feature selection have become standard practice. He has also edited influential volumes on deep learning applications, further cementing his role as a synthesizer of emerging technologies. With an h-index exceeding 60 and thousands of citations, his work bridges theoretical advances and practical deployment, making him an essential reference for researchers tackling complex, real-world problems in healthcare, cybersecurity, and software reliability.