UCSB Gevirtz Graduate School of Education
Michael J. Furlong, PhD
Project Covitality Principle Investigator of Project Covitality is a Distinguished Professor Emeritus and Research Professor at UC Santa Barbara affiliated with the International Center for School Based Youth Development. He is a past Interim Dean and an Associate Dean for Research in Gevirtz Graduate School of Education. He is a fellow of the American Psychological Association and the American Education Research Association and a member of the Society for the Study of School Psychology.
Erin Dowdy, PhD
Co-Principle Investigator of Project Covitality, is a Professor in the Department of Counseling, Clinical, and School Psychology at UCSB. She graduated from the University of Georgia in 2006 with a Ph.D. in educational psychology and an emphasis in school psychology. She is a licensed psychologist and a nationally certified school psychologist. Her research career and scholarly publications have focused on behavioral assessment, particularly universal assessment for social and emotional health and risk. She is involved in grant-funded research projects including measurement work funded by the Institute of Education Sciences investigating universal screening in schools. Dr. Dowdy has a record of past success at disseminating research findings in peer-reviewed journals with over 60 peer-reviewed publications and 70 presentations at local and national conferences. She is an associate editor for School Psychology Review.
Karen Nylund-Gibson, PhD
Co-Principle Investigator of Project Covitality, is an Associate Professor of quantitative research methodology in the Department of Education. She has been at UCSB since 2009. Prior to joining the department, she was a Postdoctoral Fellow at the Department of Mental Health at Johns Hopkins University. She earned her Ph.D. at UCLA, working with Bengt Muthen. Her research focus is on latent variable models, specifically mixture models and she has published many articles and book chapters on developments, best practices, and applications of latent class analysis, latent transition analysis, and growth mixture modeling.