About the VPAR
About the Vice Provost for Administrative Resolution
Daniel R. Jeske became Vice Provost of Administrative Resolution (VPAR) on July 1, 2019. In this role he is responsible for reviewing and resolving issues of policy, procedure, integrity and collegial relations that have the potential to impact the mission and well-being of the University. The office of the VPAR works closely with other campus offices including the offices of the Provost, Campus Counsel, Chief Compliance Officer, Ombuds, Academic Senate, and Human Resources.
Dan is a Professor in the department of statistics at UCR, and was the department chair during 2008-2015. Other campus service he has been involved with includes a two-year term as Chair of the Academic Senate Committee on Faculty Welfare and a five-year terms as the UCR Faculty Athletics Representative (2010-2015). He coordinates U.S. Navy and other industry outreach efforts for UCR Statistics. He is an elected fellow of the American Statistical Association (ASA) and served a three-year term on the ASA board of directors. He is an elected member of the International Statistics Institute (ISI), and is President-elect for the International Society of Business and Industrial Statistics (ISBIS), a society of ISI. He is the current Editor-in-Chief of The American Statistician and is an Associate Editor for Applied Stochastic Models in Business and Industry. He is a member of the Program Affiliates Committee of the National Institute of Statistical Sciences (NISS).
Dan's research interests include classification and prediction methodologies, longitudinal data modeling, statistical process control methodologies, biostatistics applications, and reliability modeling. In each of these areas his research balances theory and applications. He has supervised 22 PhD students, and he recently participated in a webinar discussion on the status of scientific p-values that can viewed here https://www.niss.org/. Within the department of statistics, Dan has been the regular instructor for the courses in statistical methods and data science.