Shan Sun-Mitchell

Shan Sun-Mitchell is a Professor in the Department of Mathematics at The University of Texas at Arlington (UTA), affiliated with the College of Science. She specializes in statistics, biostatistics, and data science with applications in health informatics and public health. Her research focuses on statistical methodologies including nonparametric procedures, kernel density estimation, and survival analysis, with notable contributions to medical applications such as cancer research and epidemiological studies.

Education: PhD in Statistics from Indiana University (1992).

Research Interests: Her work spans statistical theory and applications, including adaptive nonparametric methods, censored data analysis, and biostatistical modeling. She has led grants on topics such as biomedical informatics, liver cancer chemoprevention, and maternal health. Her research emphasizes practical applications in healthcare, such as predicting patient outcomes and optimizing clinical trial designs.

Recent Articles Trends: Her publications (2020–2023) address statistical challenges in biomedical domains, including survival analysis, kernel-based methods for censored data, and predictive modeling for health outcomes. She also explores interdisciplinary applications in sleep medicine and oncology.

• Awards:
  • Academy of Distinguished Teachers, UTA (2022)
  • College of Science Excellence in Teaching Award (2018)

Advising & Grants: Sun-Mitchell has advised over 30 graduate students and secured funding from NIH, NSF, and industry partners. Notable grants include a 2022 NIH grant for biomedical informatics training and a 2023 proposal on AI-driven dementia communication simulations.

Labs/Teams: She is a member of the Multi-Interprofessional Center for Health Informatics and leads the MS in Applied Statistics and Data Science program at UTA.