Huy Mai Source Confirmed
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
University of Arkansas at Fayetteville
faculty
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Biography and Research Information
OverviewAI-generated summary
Huy Mai investigates the intersection of machine learning, statistical modeling, and real-world data analysis. His work includes developing robust classification methods, such as a classifier designed to handle missing data under specific sample selection biases. Mai has also explored the application of deep learning models, like BERTweet, for classifying discourse on social media platforms, specifically examining the marketing of e-cigarette products. His research extends to network security, with studies on semi-supervised learning for intrusion detection and adversarial attacks against malware detection systems. He has published on feature assignment in statistical models and federated learning under sample selection heterogeneity. Mai collaborates with researchers at the University of Arkansas at Fayetteville, including Page D. Dobbs, William Baker, and Nnamdi Ezike.
Metrics
- h-index: 2
- Publications: 13
- Citations: 30
Selected Publications
- Federated Learning under Sample Selection Heterogeneity (2024) DOI
- On Prediction Feature Assignment in the Heckman Selection Model (2024) DOI
- A Robust Classifier under Missing-Not-at-Random Sample Selection Bias (2023) DOI
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study (2022) DOI
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (2022) DOI
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (Preprint) (2022) DOI
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study (Preprint) (2021) DOI
- Adversarial attacks against image-based malware detection using autoencoders (2021) DOI
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