Daniel Ries
About Daniel Ries
Daniel Ries is a Senior Statistician at Sandia National Laboratories, specializing in Bayesian Deep Learning and functional data analysis.
Title and Role
Daniel Ries holds the position of Senior Statistician at Sandia National Laboratories. He has been in this role since 2018 and operates out of the Albuquerque, New Mexico Area. His work involves significant responsibilities that rely on advanced statistical methods and data analysis.
Education and Academic Background
Daniel Ries earned his Doctor of Philosophy (PhD) and Master of Science (MS) degrees from Iowa State University. He completed his PhD from 2013 to 2017, followed by his MS from 2013 to 2015. Earlier, he obtained his Bachelor of Science (BS) degree from the University of Minnesota-Twin Cities between 2009 and 2013. This robust academic foundation underpins his current expertise and professional capabilities.
Areas of Expertise
Daniel Ries specializes in Bayesian Deep Learning and functional data analysis. His proficiency in these complex statistical fields enables him to contribute significantly to his projects at Sandia National Laboratories. His expertise is central to his role and influences the quality and scope of his work.
Collaborative Work
Known for his ability to work effectively on multidisciplinary teams, Daniel Ries often collaborates with professionals from varied backgrounds. His adaptability in learning new application subject matter showcases his versatility and enhances team outputs. This collaborative approach is a key aspect of his professional methodology.
Communication Skills
Daniel Ries is recognized for his skill in communicating complex statistical concepts to diverse audiences. This capability is essential for his role, as it ensures that intricate data insights are accessible and understandable, facilitating informed decision-making across his organization.