Erich Seamon, Ph.D.
Research ScientistInstitute for Modeling Collaboration and Innovation (IMCI)
Erich Seamon is a quantitative climatologist and data scientist, who works as a research scientist in IMCI’s geospatial modeling core initiative. Dr. Seamon has a M.S. in geological sciences from Bowling Green State University and a Ph.D. in Natural Resources from the University of Idaho, with a focus on climatological analysis, machine learning, and agricultural processes. His research focuses on statistical modeling techniques to explore natural system spatiotemporal relationships, with a particular focus on climatological impacts and their varying conditional relationships to areas such as agriculture, insurance, human health, and socio-ecological feedback systems.
Helen Brown
Clinical Associate ProfessorPublic Health and Nutrition, Exercise, Sport, and Health Sciences
Helen Brown has over 30 years of public health experience, as a nutritionist and public health generalist. She focuses on community engaged scholarship to assess, plan, and evaluate public health interventions. She leads the UI working group, Modeling Idaho Health that develops small area estimates (SAE) modeling project to identity health risk factors in Idaho counties and communities. Helen’s commitment health and justice helps inform the models that are created with this project and drives the dissemination of the results to public health leaders, change agents, and the general public.
Christopher Williams, Ph.D.
ProfessorMathematics and Statistics, University of Idaho
Christopher Williams is the Chair of the Mathematics and Statistics Departments a Professor in the Department of Statistics, and Affiliate Professor in the Bioinformatics and Computational Biology Program at the University of Idaho. Dr. Williams has taught a variety of statistics courses, and has helped many graduate students and faculty with their research as a consultant in the Statistical Consulting Center. Dr. Williams’ research areas are statistical genetics, biostatistics, and statistical methods applied to issues in natural resources. One topic of particular interest is the analysis of human twin data. Another area of interest is the estimation of disease prevalence from various types of data, such as in groups of fish that are collected and have their tissue pooled to test for disease status.
Nurbanu Bursa, Ph.D.
Postdoctoral FellowInstitute for Modeling Collaboration and Innovation (IMCI)
Nurbanu Bursa is a postdoctoral fellow in the Institute for Modeling, Collaboration, and Innovation at the University of Idaho and one biostatistician member of the Mountain-West Clinical & Translational Research Infrastructure Network Program. She completed her M.Sc. and Ph.D. at the Department of Statistics, Hacettepe University, Turkey. Her academic research interests lie primarily in statistical modeling for real and large datasets from health, renewable energy, climate change, social media research, and finance using many statistical techniques such as data and text mining, machine learning, multivariate statistics, nonparametric statistics, probabilistic distributions, time series, survival analysis, and survey analysis. She has a lot of nationwide project experience with medical doctors who work in the Republic of Turkey Ministry of Health and forest engineers.
Mohamed Megheib, Ph.D.
Postdoctoral FellowInstitute for Modeling Collaboration and Innovation (IMCI)
Mohamed Megheib is a statistician and data scientist, who is working as a postdoctoral fellow in Institute for Modeling Collaboration and Innovation (IMCI). Mohamed holds a Ph.D. and a M.S. in Statistics from George Washington University; a M.S. in Statistics from Cairo University; and a B.Sc. in major of Statistics and minor of Economic from Cairo University. He has over 10 years of experience in applied statistics, as a statistician at different international and local organizations. His research areas are parametric and nonparametric modelling, modelling of correlated data, spatial statistics, composite indicators, designing questionnaires, survey research, model comparison, misspecification, Bayesian inference, econometrics and applications of statistics in social sciences.