Lybarger People
Faculty
Kevin Lybarger
Assistant Professor
Dr. Kevin Lybarger's research centers on artificial intelligence (AI) and natural language processing (NLP), particularly within healthcare applications. His interests span clinical informatics, health-oriented conversational agents, and public health. His broader research includes information integrity and correctional system informatics, using textual data to support decision-making, improve information quality, and enable innovative information exchange with societal impact. Dr. Lybarger earned his PhD in Electrical and Computer Engineering from the University of Washington, an MS from the University of Colorado Boulder, and a BS from Seattle University. He completed a National Library of Medicine Postdoctoral Fellowship at the University of Washington School of Medicine.
Students
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Md. Mushfiqur Rahman
PhD Student
Muhammad is a fourth-year CS PhD student at GMU, specializing in NLP, computer vision, and machine learning. His research explores linguistic diversity in language models, patient-interaction simulations, and text simplification. He has authored eight peer-reviewed papers, including Q1 journals and ACL workshop publications. During his internship at the US Naval Research Laboratory (2023-2024), he developed a GAN-based image denoiser for the EUV Image Spectrometer on the Hinode spacecraft. He holds a master's in Machine Learning from GMU and a bachelor's from the Islamic University of Technology, Bangladesh.
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Hadeel Elyazori
PhD Student
Hadeel is a fourth-year PhD student in Information Technology at George Mason University, specializing in natural language processing in clinical settings and correctional systems. As a recipient of the IDIA fellowship, she focuses on the implementation of motivational interviewing techniques in clinical settings, exploring methods to improve patient engagement and healthcare outcomes. She holds a master's degree in Applied Information Technology with a Machine Learning concentration from GMU, and a bachelor's degree in Computer Science from the American University of Beirut.
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Mohammad Sabik Irbaz
PhD Student
Mohammad is a PhD student at George Mason University, specializing in natural language processing with a focus on medical applications. His research areas include text simplification, text style transfer, and clinical machine learning. He received his bachelor's degree in Computer Science and Engineering from the Islamic University of Technology, Bangladesh, in 2021. Following his BSc, he spent around 2.5 years in the data science industry, working as a Data Scientist at Leadbook and a Lead Machine Learning Engineer at Omdena.
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Saadat Hasan Khan
PhD Student
Saadat is a PhD student in Computer Science at George Mason University, specializing in natural language processing and its applications in healthcare. His work focuses on optimizing predictive language models and applying AI to real-world challenges in healthcare. In the summer of 2024, he interned as a Machine Learning Engineer at Brillient Corporation, where he contributed to building RAG pipeline-based medical conversational agents. Before joining GMU, he served as a lecturer for three years at Brac University, Bangladesh, under the supervision of Dr. Mahbubul Majumdar. He completed his BSc at Brac University in 2019, graduating with the Vice Chancellor's Medal.
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Md Tanvir Rouf Shawon
PhD Student
Tanvir is a PhD student in Computer Science at George Mason University, specializing in natural language processing and healthcare-focused AI. His research explores LLM-based patient simulation and clinically reliable medical conversation systems. He focuses on developing multi-agent frameworks and evaluation methods to ensure safety, interpretability, and practical deployment of conversational AI systems in real healthcare contexts. Before pursuing his PhD, he served as a Lecturer in the Department of CSE at Ahsanullah University of Science and Technology (AUST), Bangladesh, for three years. He completed his BSc from AUST, graduating with the Dean's Award for academic excellence.