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About:

Ghaith Husari, Associate Professor of the Department of Computing at East Tennessee State University, performs research focusing on using machine learning  and data analytics to address pressing research challenges in healthcare. His research emphasizes the application of AI and data-driven models to predict cardiovascular risks and improve heart disease diagnostics. By integrating machine learning algorithms with large-scale healthcare data, Dr. Husari aims to develop more accurate predictive models that can significantly enhance patient outcomes and support clinical decision-making.

Dr. Husari's research lies at the intersection of machine learning and computer vision. His work utilizes images, videos, and audio to detect diseases, unauthorized intrusions, and healthcare outcomes. Committed to interdisciplinary collaboration, Dr. Husari partners with healthcare professionals and data scientists to develop innovative solutions tailored to real-world medical challenges. His contributions extend beyond academia through impactful publications and by mentoring the next generation of data scientists, equipping them with essential skills for the evolving field of data analytics.

Education:

Ph.D. in Software and Information Systems– UNC Charlotte, 2019

Research & Interests:

Machine Learning, Data Analytics, Healthcare Analytics, Computer Vision and Artificial Intelligence.

Courses Taught:

Data Analytics and Visualization

Information Security and Privacy

Data Management

Ethical Hacking and Pen Testing

Cybersecurity Risk Governance

Network and Information Security 

Social Media Analytics

Advanced Concepts in Database

Publications:

Factors Associated With Myocardial Infarction in a Rural Population With Peripheral Arterial Diseases. Angiology Journal. 2024;0(0). doi:10.1177/00033197241232608

Pattern of liver disease in hospitalized patients with cardiometabolic comorbidities: A United States experience. American Public Health Association (APHA 2023).

CommunityShield AI: An Integrated AI-Based Security System for Public Safety Enhancement, ASRP 2023

Machine Learning Algorithms And Their Applications in Classifying Cyberattacks on a Smart Grid Network, 2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)

Feed-Forward Intrusion Detection and Classification on a Smart Grid Network, 2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC)

Machine learning predictive analytics for player movement prediction in NBA: applications, opportunities, and challenges. In Proceedings of the 2021 ACM Southeast Conference (ACMSE '21). 

Thor: A Deep Learning Approach for Face Mask Detection to Prevent the COVID-19 Pandemic, IEEE SoutheastCon 2021.