ProfessorsProfessors of University of HoustonXin Zhou

Xin Zhou

University of Houston

H-index: 4

North America-United States

About Xin Zhou

Xin Zhou, With an exceptional h-index of 4 and a recent h-index of 4 (since 2020), a distinguished researcher at University of Houston, specializes in the field of Artificial Intelligence, Generative AI, AI-Security, Data Science.

His recent articles reflect a diverse array of research interests and contributions to the field:

AviationGPT: A Large Language Model for the Aviation Domain

All Models are Wrong, but Some (times) are Useful: Evaluating when Machine Learning Models are Useful for Detecting Novel Malware in the Wild.

MalGen: Malware Generation with Specific Behaviors to Improve Machine Learning-based Detectors.

Software Vulnerability Detection via Multimodal Deep Learning

Vulnerability detection via multimodal learning: Datasets and analysis

Malware Generation with Specific Behaviors to Improve Machine Learning-based Detection

SAGE Intrusion Detection System: Sensitivity Analysis Guided Explainability for Machine Learning.

Phishing Sites Detection From a Web Developer’s Perspective Using Machine Learning

Xin Zhou Information

University	University of Houston
Position	PhD student
Citations(all)	34
Citations(since 2020)	34
Cited By	4
hIndex(all)	4
hIndex(since 2020)	4
i10Index(all)	1
i10Index(since 2020)	1
Email	Access Email
University Profile Page	University of Houston
Google Scholar	View Google Scholar Profile

Xin Zhou Skills & Research Interests

Artificial Intelligence

Generative AI

AI-Security

Data Science

Top articles of Xin Zhou

Title	Journal	Author(s)	Publication Date
AviationGPT: A Large Language Model for the Aviation Domain	arXiv preprint arXiv:2311.17686	Liya Wang Jason Chou Xin Zhou Alex Tien Diane M Baumgartner	2023/11/29
All Models are Wrong, but Some (times) are Useful: Evaluating when Machine Learning Models are Useful for Detecting Novel Malware in the Wild.		Michael Smith Raga Krishnakumar Joseph Lubars Stephen Verzi Xin Zhou ...	2022/10/1
MalGen: Malware Generation with Specific Behaviors to Improve Machine Learning-based Detectors.		Michael Smith Armida Carbajal Eva Domschot Nicholas T Johnson Akul Goyal ...	2022/10/1
Software Vulnerability Detection via Multimodal Deep Learning		Xin Zhou Rakesh M Verma	2022/9/29
Vulnerability detection via multimodal learning: Datasets and analysis		Xin Zhou Rakesh M Verma	2022/5/30
Malware Generation with Specific Behaviors to Improve Machine Learning-based Detection		Michael R Smtith Stephen J Verzi Nicholas T Johnson Xin Zhou Kanad Khanna ...	2021/12/15
SAGE Intrusion Detection System: Sensitivity Analysis Guided Explainability for Machine Learning.		Michael R Smith Erin Acquesta Arlo Ames Alycia N Carey Christopher R Cuellar ...	2021/9/1
Phishing Sites Detection From a Web Developer’s Perspective Using Machine Learning		Xin Zhou Rakesh Verma	2020/1/7
PhishBench 2.0: A Versatile and Extendable Benchmarking Framework for Phishing		Victor Zeng Xin Zhou Shahryar Baki Rakesh M Verma	2020/10/30
Using neural architecture search for improving software flaw detection in multimodal deep learning models	arXiv preprint arXiv:2009.10644	Alexis Cooper Xin Zhou Scott Heidbrink Daniel M Dunlavy	2020/9/22
Joint Analysis of Program Data Representations using Machine Learning for Improved Software Assurance and Development Capabilities		Scott Heidbrink Kathryn Nicole Rodhouse Daniel Dunlavy Alexis Cooper Xin Zhou	2020/9/1