H
Huy Mai Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
faculty
2 h-index
13 pubs
30 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Huy Mai's research focuses on the application of machine learning and data analysis techniques to address complex problems across various domains. His work includes developing and evaluating robust classification models, particularly in areas affected by sample selection bias and missing data, as seen in studies on the Heckman selection model and classifiers under missing-not-at-random conditions. Mai also investigates the use of advanced deep learning methods, such as BERTweet, for analyzing social media discourse, including research on e-cigarette marketing on Twitter and the classification of vaping-related content. His research extends to network security, with work on semi-supervised spatial-temporal feature learning for anomaly-based intrusion detection, and adversarial attacks against malware detection systems. Mai has collaborated with researchers at the University of Arkansas at Fayetteville, including Page D. Dobbs, William Baker, and Nnamdi Ezike, on multiple publications.
Metrics
- h-index: 2
- Publications: 13
- Citations: 30
Selected Publications
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Federated Learning under Sample Selection Heterogeneity (2024)
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On Prediction Feature Assignment in the Heckman Selection Model (2024)
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A Robust Classifier under Missing-Not-at-Random Sample Selection Bias (2023)
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Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study (2022)
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Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (2022)
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Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (Preprint) (2022)
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Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study (Preprint) (2021)
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Adversarial attacks against image-based malware detection using autoencoders (2021)
Collaboration Network
Top Collaborators
Page D. Dobbs
University of Arkansas at Fayetteville
4 shared publications
In database
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study (Preprint)
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (Preprint)
Brian A. Primack
Oregon State University (US)
4 shared publications
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study (Preprint)
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (Preprint)
Justin Zhan
University of Arkansas at Fayetteville (US)
3 shared publications
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study
- Adversarial attacks against image-based malware detection using autoencoders
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study (Preprint)
Xintao Wu
University of Arkansas at Fayetteville
3 shared publications
In database
- A Robust Classifier under Missing-Not-at-Random Sample Selection Bias
- On Prediction Feature Assignment in the Heckman Selection Model
- Federated Learning under Sample Selection Heterogeneity
William Baker
University of Arkansas at Fayetteville
2 shared publications
In database
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study (Preprint)
Jason B. Colditz
University of Pittsburgh (US)
2 shared publications
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study (Preprint)
Shyam Visweswaran
University of Pittsburgh (US)
2 shared publications
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study
- Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study (Preprint)
Nnamdi Ezike
University of Arkansas at Fayetteville
2 shared publications
In database
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (Preprint)
Allison J. Ames
University of Arkansas at Fayetteville (US)
2 shared publications
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series
- Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series (Preprint)
Du Wei
University of Arkansas at Fayetteville (US)
2 shared publications
- A Robust Classifier under Missing-Not-at-Random Sample Selection Bias
- A Robust Classifier Under Missing-Not-At-Random Sample Selection Bias
Xintao Wu
2 shared publications
- A Robust Classifier Under Missing-Not-At-Random Sample Selection Bias
- On Prediction Feature Assignment in the Heckman Selection Model
Alycia N. Carey
University of Arkansas at Fayetteville
1 shared publication
In database
- Adversarial attacks against image-based malware detection using autoencoders
Asif Mehmood
United States Air Force Research Laboratory (US)
1 shared publication
- Adversarial attacks against image-based malware detection using autoencoders
Wen Huang
1 shared publication
- A Robust Classifier Under Missing-Not-At-Random Sample Selection Bias
Wen Huang
University of Arkansas at Fayetteville
1 shared publication
In database
- A Robust Classifier under Missing-Not-at-Random Sample Selection Bias
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