Farrokh Alemi was trained as an operations researcher and industrial engineer and has worked in both academia and health industry. He maintains patents on (1) sentiment analysis, (2) measurement of episodes of illness and (3) personalized medicine. He has more than 105 peer reviewed publications in journals such as Health Services Research, Medical Care, and Palliative Medicine. His research focuses on causal analysis of massive data available in electronic health records. This research has required balancing of data to estimate causal impact of interventions. His publications have contributed to predictive medicine, precision medicine, comparative effectiveness of medications, sentiment analysis, natural language processing, risk adjusted analysis of cost effectiveness, causal networked models, identifying trajectories of diseases, and predicting prognosis of patients with multiple morbidities. Dr. Alemi is the author of the widely used Multi-Morbidity index. He has worked with diverse groups of patients including children, nursing home residents and patients with diabetes, major depression, heart failure, anemia, hypertension, trauma, drug abuse, and other diseases. In addition, Dr. Alemi was a pioneer in online management of patients and has provided Congressional testimony on role of Internet in health delivery. He is the author of a book on decision analysis and another on policy systems and a third on application of process improvement to personal health. A fourth book, on causal statistical analysis was published in 2021. Dr. Alemi can be reached at falemi@gmu.edu .

Dr. Wojtusiak, Associate Professor of Health Informatics and Director of the Machine Learning and Inference Laboratory, has research expertise that includes machine learning, health informatics, artificial intelligence in clinical decision support and knowledge discovery in medical data, evolutionary computation, knowledge mining, health data analytics, and a wide range of applications of these fields in health care. His particular area of interest is in developing algorithms that derive simple and transparent models from complex health data to predict patient and population outcomes. He studies how to create and evaluate reproducible, unbiased and trustworthy algorithms and models. Dr. Wojtusiak serves as the Division Director for Health Informatics in the Department of Health Administration and Policy. He oversees undergraduate, master's and doctoral programs in health informatics. Dr. Wojtusiak teaches several courses focused on machine learning, data mining, artificial intelligence and computing applied in medicine, healthcare and individual/population health. He authored or co-authored over 100 research publications and presentations and continues to collaborate with multiple national and international institutions.

Dr. Goldberg is a mixed methods researcher with expertise in organizational behavior and change management. Her research focuses on adoption and implementation of innovative care delivery models and health information technology, such as the patient-centered medical home, team-based care, performance measurement, electronic health records, and other electronic systems for quality improvement. She has published more than 30 articles in peer reviewed medical and public health journals, authored three peer reviewed textbook chapters, and presented more than 40 workshops and seminars throughout North America and Europe. Her experience includes research from academic and healthcare management consulting environments. This experience includes conducting research and evaluation of healthcare services for the federal government, including agencies under the Department of Health and Human Services (DHHS), the Department of Veterans Affairs (VA), and the Department of Defense (DoD).

Jee Vang is a data scientist focused on architecting, implementing, and using Big Data and cloud computing technologies to store and process massive and high-dimensional data towards learning causal and predictive models. He is currently focused on applying cloud analytics solutions in the area of medical and healthcare informatics. His research projects include discovering and learning causal relationships between socio-demographics, diagnoses, medication, and mortality and/or healthcare outcomes. His most recent research spans COVID-19 and depression treatment. His developing passion is in community activism in the area of STEAM education for K-12 and advanced training for working professionals.

Dr. Min's research interest is in the areas of ontology construction and its applications in bioinformatics. She has developed structural methodologies for auditing medical ontologies such as UMLS, NCI Thesaurus, and SNOMED CT. She has also explored ontology applications as a formal mechanism for representing and implementing behavioral models in computer systems. She is currently exploring the expansion of ontology applications, including ontology-based data integration, ontology- based machine learning methods, data extraction and analysis from various EHR systems, and other computer science technologies to clinical and health informatics.

Dr. Coffin is an Adjunct Professor in Health Informatics at George Mason University. He is the Founder & CEO of Celtiq, LLC. His background is in Health Research Science with a concentration in Knowledge Discovery and Health Informatics. In this role at Celtiq, Dr. Coffin advises the federal organizations on issues related to healthcare, strategic planning, acquisition, technology development, national security and anti-terrorism. He conducts health and technology assessments and consequence analyses for federal agencies including: the military services, OSD, DHS, the Federal Reserve, the Departments of Treasury, Agriculture, and Transportation and various intelligence agencies. He has supported the DDR&E and Defense Science Medical Board for TBI and PTSD with such programs as one to develop mission specific body armor. He has provided disability evaluations for the Army Combat Related Specialty Compensation and Traumatic SGLI (TSGLI) programs. His research work includes machine learning and AI modeling to detect rare diseases, depression, and opioid addiction. In other areas, he led teams of industry experts to develop vulnerability analyses for US critical infrastructure including healthcare & telecommunication networks, public utility systems and public and private financial networks. Dr. Coffin has taught classes in Health Informatics, Health System Delivery, SQL programming, Health Policy, and Continuous Quality Improvement.

Akbar Soleiman has a Ph.D. in Nutrition, for 15 years was a faculty member back in his country, and has several peer-reviewed publications in this field. He is now at George Mason University in the Health Informatics program (MSc.) and very interested in health data analysis. Before coming to GMU, he had a postdoc position at Howard University and was working on the nutritional effects of Saffron on Colorectal cancer in African-American. He also has publications in this subject. Now he concentrates on the Health Informatics program, data analysis, data mining, and Clinical Decision Support Systems (CDSSs).

Ghaida is a PhD student at George Mason University studying Health Services Research with a concentration in Knowledge Discovery and Health Informatics. She received a Master of Science in Health Informatics with a concentration in Health Data Analytics and a degree in Bachelor of Science in Health Administration with a concentration in Health Systems Management from George Mason University.

Currently she works as a research assistant generating feedback text and graphics in Python for a depression aid tool. Prior to starting her doctoral program, Ghaida volunteered as a Medical Scribe at the Mason and Partners COVID-19 vaccine clinic. Before that, she was an Operations Assistant at the University of George Mason's INTO University Partnerships where she provided administrative and operational support, and managed tasks that involve supporting international students.

Sai Keerthi is a dentist and holds a master's degree in Health Informatics with concentration in Data Analytics from George Mason University. Her research interests are Data mining, big data analysis in health services research, and promoting patient-provider management using online tools. LinkedIn profile: www.linkedin.com/in/saikeerthi-kalluri

She received a Master of Science in Health Informatics with a concentration in Health Data Analytics from George Mason University. Her Bachelor's degree was in Computer Information Systems. Her enjoyment of problem-solving and helping people has led her to healthcare. In her studies, she has experience with EMR systems and Python, SQL, R, STATA, Tableau, Classification Systems, Interoperability Standards and Vocabularies, and analyzing health data such as SEER and Claims data. Her interest in healthcare stems from her goal to help streamline healthcare between the patient and the provider without compromising quality or individualization. She is passionate about making a meaningful impact on the healthcare industry through innovation and forward-thinking approaches.

Sophia is pursuing a Bachelor's degree in Psychology from the University of Virginia. Her interest in health and wellness has led her to become a certified yoga instructor and join the Safety and Wellness committee of UVA's Student Council. She also has a background in social media marketing and video production. Her experiences growing her YouTube channel have encouraged her to become involved with the Marketing Committee of UVA's Second Year Council as well as become the YouTube chair of WUVA, a multimedia news organization.

She is currently pursuing a master's degree in Health Informatics with Data Analytics concentration at George Mason University. She holds a bachelor's degree in Dentistry. Her research interests are big data analysis in health service research, machine learning and data mining, and promoting patient-provider management using online tools. She is passionate about leading the healthcare industry to new heights through her innovations and ideas.

Renu Karmacharya is pursuing Master's degree in Health Informatics with Data Analytics at George Mason University. She holds Bachelor's degree in Nursing. She has experienced with various comorbidities in diverse groups of patients from pediatric to geriatric population in both health care setting and community-based settings. Her research interests are impact of health informatics in chronic conditions, prediction of pandemic with the use of data mining, machine learning in health care, and big data analysis in health care services. She is enthusiastic about combining her health care experience with health informatics/data analytics to improve health outcomes and reduce overall health care cost.