Dr. Chyng-yang Jang is an associate professor in the Department of Communication at the University of Texas at Arlington. He received his Ph. D. in Information and Media from Michigan State University. His research interests center on the uses and effects of information and communication technology such as groupware, blog, and social media, in various contexts including health communication, marketing communication, relational communication, and teamwork. He is passionate in learning how people use information technology and how technology can be better designed to bring positive impacts to people’s personal and organizational lives. His recent research efforts focus on health information seeking and health promotion related to HPV and COVID-19 vaccination. At UTA, Dr. Jang also serves as the coordinator for the Communication Technology majors. He teaches courses on Web design, Internet marketing and data analytics. He supervises undergraduate student teams in building Websites and applications for local businesses and organizations.

Katherine “Kat” A. Kreis, MSN, RN, CHSE, is a Clinical Assistant Professor at the University of Texas at Arlington (UTA), in the College of Nursing and Health Innovation (CONHI) Smart Hospital Facility. As a member of the Clinical Simulation Faculty team, she uses simulation-based experiences (SBE) to improve learner outcomes among those enrolled in prelicensure clinical nursing courses at UTA CONHI. While pursuing a PhD in Nursing, she is building a research program focusing on reducing medication errors among student nurses through the integration of health-related technology in SBE. Ms. Kreis has presented on a variety of simulation topics at both the national and international level. She is the current Vice President for Delta Theta Chapter 102 of Sigma Theta Tau, the International Honor Society of Nursing. As a strong advocate for Simulation Based Mastery Learning (SBML) she is also a member of several simulation related organizations including International Association for Clinical Simulation and Learning (INACSL), the Association of Simulated Patient Educators (ASPE), and the Society for Simulation in Healthcare (SSH). 

Dr. Liao is an Assistant Professor of the Public Health Program in the Department of Kinesiology, University of Texas at Arlington. Dr. Liao’s research interests include leveraging mobile technology and wearable sensors to capture daily behaviors such as physical activity, sedentary behavior, eating, and sleep, and to investigate the contextual and psychosocial determinants of those behaviors in our everyday life. Her current research focuses on the development of personalized interventions using data from wearable biosensors to promote physical activity to reduce the risk of obesity-related chronic diseases, as well as in insufficiently active cancer patients to improve their quality of life after cancer.

Dr. Liao completed a competitive postdoctoral fellowship in colorectal cancer prevention at The University of Texas MD Anderson Cancer Center after receiving her PhD in Health Behavior Research from University of Southern California. She received her Master in Public Health degree in Biostatistics from The University of Texas Health Science Center at Houston. Dr. Liao was the recipient of the Mentored Junior Faculty Fellowship at MD Anderson and a fellow of the National Cancer Institute’s Transdisciplinary Research on Energetics and Cancer (TREC). Dr. Liao now directs the Physical Activity and Wearable Sensors (PAWS) lab at UT Arlington.

Shirin Nilizadeh is Assistant Professor at the Department of Computer Science and Engineering, University of Texas at Arlington. She received her Ph.D. in Security Informatics from the Indiana University Bloomington (IUB). For her dissertation on Privacy-aware Decentralized Architectures for Socially Networked Systems, she received a two-year fellowship from the School of Informatics and Computing at IUB. Following her doctorate, she held post-doctoral positions in CNets at IUB from 2014-2015, in SecLab at University of California Santa Barbara from 2015-2017, and then in CyLab at Carnegie Mellon University from 2017-2018. She conducts data-driven research to study online security, privacy, and safety. Her research is interdisciplinary and spans across multiple areas, from traditional security and privacy research to social computing and Health Informatics. 

Jennifer Roye, MSN, RN, CHSE, CNE is The Assistant Dean for Simulation and Technology and a Clinical Assistant Professor at the University of Texas at Arlington College of Nursing and Health Innovation. She is lead faculty for the Fundamental Telehealth Skills course in the Health Informatics Certificate Program. Mrs. Roye received her MSN from UTA in 2003 and is currently enrolled at The University of Alabama in the EdD Instructional Leadership program. She practiced as a CPNP in private practice for 10 years and as an RN in the Emergency Department at Cook Children’s Medical Center in Ft. Worth, Texas for 16 years. Her areas of research interest include simulation, telehealth, student engagement, enhancing online education, health informatics, and moral distress in the undergraduate nursing student population.

Dr. Peggy Semingson is an associate professor in the Department of Linguistics and TESOL at The University of Texas at Arlington where she teaches courses in TESOL. Her Ph.D. is in Curriculum and Instruction with a specialization in Language and Literacy Studies from The University of Texas at Austin in 2008. Research interests include digital pedagogies, media-based learning, online learning, and remote/virtual ESL teaching and learning. Current research studies include COVID Health literacy and multimodal texts and materials and  the ways that we can use digital and innovative pedagogies to engage teachers to most effectively help them to teach in their current and future classroom contexts. Within this area, she is more specifically interested in socially distributed knowledge sharing that takes place online, distributed cognition, and video-mediated (e.g., YouTube) discussion and dialogue. Her longstanding education-focused YouTube channel has over two million views of original video content and over 5,000 subscribers.

Dr. Shan Sun-Mitchell is a Distinguished Teaching Professor in the Department of Mathematics.

She is also Program Director for the MS in Applied Statistics and Data Science.

Dr. Wang is Jenkins-Garratt Professor of Statistics and Data Science at Department of Mathematics and Director of Research in Division of Data Science, College of Science.  Her research interests include Bayesian modeling and inference, statistical omics, machine/deep learning and AI, integrative and meta- analysis, and order-related sampling design, theory, and inference.

Dr. Wang has rich experience in developing and applying statistical and computational methods for analysis of complex and diverse data. She leverages this expertise to extensively collaborate with researchers across various fields, including biomedicine, health care, business, computer science, engineering, chemistry, physics, and mathematics. She has coauthored over 90 peer-reviewed publications, many in prestigious statistical and science journals. Her research projects have been generously supported by external funding, including NCI R01, NIGMS R15, NIDA R21 and R33, NSF-DMS grants. In 2020, she was honored with the Gerald J. Ford Senior Research Fellowship, recognizing the significance of her scholarly contributions. In 2024, she was recognized as an elected fellow of the American Statistical Association, one of the highest honors in the statistics and biostatistics profession.

Dr. Wang is deeply committed to mentoring the next generation of researchers. She has directed 20+ Ph.D. theses and co-directed three, served on the committees of 30+ Ph.D./master’s students. All her graduates successfully established independent careers in academia, industry, and tech in the US. She has also been actively mentoring junior faculty and post-docs in developing their research programs. Since she joined UTA in 2023, she has led efforts on various data science initiatives.