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ABOUT THE CAIT CENTER

Advancing AI and Technology Education Through Research

AI and technology are reshaping how information is documented, interpreted, communicated, and used to support decision-making. As new tools continue to emerge, professionals need clear, evidence-informed guidance that explains how these systems function, how to evaluate them responsibly, and how to use them effectively in real-world settings. The Collaborative AI Technology Center (CAIT Center) was created to address this need. Our mission is to provide research-backed education that brings clarity to the AI and technology tools transforming today’s work environments. We focus on practical understanding, real-world context, and the essential concepts that help professionals navigate an evolving technological landscape. The CAIT Center is built through collaboration between the GW Biomedical Informatics Center and the University of Maryland Eastern Shore School of Pharmacy. These institutions are recognized leaders in AI, technology, and bioinformatics research, and their combined expertise allows us to develop high-quality educational programs and certifications that support today’s workforce and prepare individuals for the changes ahead.

Research-Based Instruction
Flexible, Self-Paced Learning
Lifetime Access
Skill-Building for Modern Technologies

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INSTRUCTORS

Researchers and Instructors

Our courses are taught and developed by university researchers and instructors with expertise in AI, technology, and applied informatics.

Vahab Khademi Shamami, PhD

Postdoctoral Researcher, Biomedical Informatics Center George Washington University School of Medicine and Health Sciences

Dr. Shamami is a researcher with expertise in statistics, applied mathematics, and machine learning in healthcare. He earned a Ph.D. in Measurement & Statistics and master’s degrees in Applied Mathematics and Statistics from the University of Massachusetts. His work spans applications of statistical and machine learning modeling in both academia and industry, including social determinants of health, disease prognosis modeling, and bias detection in algorithms. Dr. Shamami contributes to study design and implementation of statistical analyses, develops and applies machine learning models for research data, and supports interpretation and reporting of results for manuscripts and presentations. He is particularly interested in the theory of AI and machine learning and applying these methods to improve health and medical research.

Phillip Ma, MD

Assistant Research Professor, Biomedical Informatics Center George Washington University School of Medicine and Health Sciences

Dr. Ma is an Assistant Research Professor at the George Washington University School of Medicine and Health Sciences and a Research Associate at the Washington DC VA Medical Center. He works with healthcare and informatics data, extracting and transforming electronic health records and building machine learning models for prediction and classification. He has contributed to multiple peer‑reviewed publications and to research funded by the VA Health Services Research & Development program and the National Institutes of Health. Dr. Ma earned a B.A. in Biology and Economics from Rutgers University and an M.D. in 2019 from the American University of Integrative Sciences, where he also assisted in the Pharmacology department. He applies his clinical background and skills in Python, SQL, and machine learning to informatics research at the Biomedical Informatics Center.

Senait Tekle, PhD

Research Fellow, Biomedical Informatics Center George Washington University School of Medicine and Health Sciences

Dr. Tekle is a research fellow at the Biomedical Informatics Center at the George Washington University. She holds a PhD in Prevention Science from Washington State University and has completed postdoctoral training through GW’s Primary Care Research Program (P-CART). Her research focuses on implementation science, with an emphasis on translating health interventions into effective and sustainable practice in real-world settings. Her work examines how evidence-based programs can be adapted, evaluated, and scaled to fit clinical and community contexts. Dr. Tekle currently contributes to two federally funded NIH AIM-AHEAD projects that use artificial intelligence to support behavioral and community health. One of these projects focuses on the use of explainable AI to improve trust in AI models and to detect bias in biomedical and behavioral research, with a specific focus on Alzheimer’s Disease and Related Dementias. Through this work, she is involved in research design, data analysis, and collaboration with interdisciplinary partners to support the ethical and responsible use of AI in healthcare research.

T. Sean Vasaitis, Ph.D., M.S. EHS

Dean and Professor, School of Pharmacy and Health Professions University of Maryland Eastern Shore

Dr. Vasaitis became the Dean of the School of Pharmacy and Health Professions in 2023. He joined the UMES School of Pharmacy as a founding faculty member in 2010, and was Assistant Dean for Student Affairs in the School of Pharmacy from 2017 – 2021. Dr. Vasaitis completed his doctoral work in Pharmacology and Experimental Therapeutics at the University of Maryland School of Medicine in 2007. He holds a masters degree in Exercise and Health Science from Miami University, Ohio and a bachelors degree in Biology from the University of Maryland, Eastern Shore. Prior to his appointment at the UMES School of Pharmacy, he completed two research fellowships. The first was in Cancer Drug Discovery with the world-renowned Dr. Angela Brodie and Dr. Vincent Njar, which continued his work in the development of novel inhibitors of androgen action for the treatment of prostate cancer. His second fellowship involved clinical & translational research in the Geriatric Research, Education and Clinical Center at the Baltimore Veterans Affairs Medical Center, investigating the mechanisms by which exercise, vitamin D and complementary therapeutics affect metabolic function and glucose homeostasis. Dr. Vasaitis’ research goals follow the overarching concept of integrating Western approaches to medicine and pharmacological therapy with evidence-based complementary medicine to further a holistic approach to disease treatment. Vasaitis is also a taijiquan (tai chi) enthusiast in the lineage of Chen Bing of Chenjiagou. In addition to his research in novel drug development and metabolic function, he has taught tai chi to patients with Parkinson’s disease, stroke, cancer, multiple sclerosis, cardiovascular disease and diabetes as part of studies with Johns Hopkins Prohealth, the University of Maryland School of Medicine, and within his own business practice. He previously held weekly classes through the UM Center for Integrative Medicine from 2005 to 2020 and continues to coordinate the Complementary and Alternative Medicine course in the UMES School of Pharmacy.

Ying Yin, PhD

Assistant Research Professor, Biomedical Informatics Center George Washington University School of Medicine and Health Sciences

Dr. Yin received her Pharmacology Ph.D. from the School of Medicine, Temple University, in 2013. After graduation, she spent 7 years as an excellent consultant specializing in data analysis and data visualization, serving clients in diverse industries. In 2020, she joined GWU as a post-doctoral researcher. Her background in biomedical science and applied experience in data management and data analytics prepared her to solve medical informatics problems in a real-world setting. By collaborating with the clinical experts, her research focuses on leveraging the big data sets available through electronic health records and performing retrospective and/or predictive studies using machine learning and statistical methods to summarize, compare, and predict clinic outcomes of different patient cohorts.

Qing Zeng, PhD

Director, Biomedical Informatics Center Professor, Department of Clinical Research and Leadership, George Washington University School of Medicine and Health Sciences

With 20 years of experience in informatics, Dr. Zeng has special expertise in text mining, consumer health informatics, and semantic integration of data sources. She has published over 150 peer-reviewed articles, as well as served as the PI and Co-PI on a number of VA HSR&D, NIH, and DOD-funded research projects. Dr. Zeng's research vision is to leverage information for healthcare research and delivery. Her main research areas are NLP and consumer health informatics. Several of her papers have been selected by the International Medical Informatics Association's Yearbook and one paper won the Distinguished Paper Award in the 2011 American Medical Informatics Association's Joint Summit. In 2014, her "HeartsLikeMine" project won first place in the "Ideas That Work" contest at the iHealth Conference sponsored by the American Medical Informatics Association and Academy Health. Prior to coming to GW, Dr. Zeng was a Professor at the University of Utah and an Associate Professor at Harvard Medical School, where she developed an NLP tool (HITEx) for two large consortium projects (i2b2 and SPIN). HITEx was the first open-source, comprehensive clinical NLP system in the nation. In addition to her work at GW, Dr. Zeng is currently the Associate Director of the Center for Health and Aging at the Washington DC VA Medical Center. At the VA, she has organized a VA-wide collaboration to develop interoperability standards for the broader clinical NLP community. The Open Access Collaborative (OAC) Consumer Health Vocabulary (CHV) produced by her team is the first and only consumer health vocabulary that has been incorporated into the Unified Medical Language System. She has also developed a number of novel informatics methods (e.g. automated illustration of instruction and social media analysis) to improve patient-centered care.

Linda Zanin, EdD

Adjunct Professor, Department of Clinical Research and Leadership George Washington University School of Medicine and Health Sciences

With 32 years in higher education and building community partnerships, Dr. Zanin currently serves as the Director of Strategic Partnerships. In her role, she connects and supports academics, researchers, and community members to facilitate, grow, and strengthen community-engaged research. Dr. Zanin supports community–academic partnerships, gathers community input for academic research, and increases research in community settings that are responsive to health pressing health disparities. The success of her work is based on the value placed on researchers and community members being engaged, connected, equipped with the resources they need, and informed of new opportunities to work together. To meet the goal of increasing community engagement, Dr. Zanin ensures relevance by promoting the development of research and outreach strategies that matter to the communities. She promotes trust between communities and academic partners, expanding the understanding of research and what it means to participate and collaborate in research activities. Dr. Zanin aims to increase the knowledge, awareness, and ability of community members and researchers to implement and disseminate research.

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Demystifying AI for Health Professionals

09/7/26

About Us

Advancing AI and Technology Education Through Research

Vahab Khademi Shamami, PhD

Phillip Ma, MD

Senait Tekle, PhD

T. Sean Vasaitis, Ph.D., M.S. EHS

Ying Yin, PhD

Qing Zeng, PhD

Linda Zanin, EdD

Demystifying AI for Health Professionals

Advancing AI and Technology Education Through Research

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