Robert J Records

Robert J Records

ARM Technical Lead & Operations Manager

Bio

Robert Records has worked at ORNL for 14 years, during which he has managed a variety of different projects with titles such as Team Leader, Technical Lead, Project Manager, and Program Manager for the Department of Homeland Security and the Department of Energy.  In recent years, Rob has been the Operations Manager for the Atmospheric Radiation Measurement Program (ARM) Data Center.  The ARM Data Center is an important component of the ARM facility where data collected in the field at ARM observatories, at locations around the world, are routed, processed, archived, and made available to the science user community. Rob began supporting the ARM Data Center in 2012 and assumed the role of ARM Data Center Technical Leader in 2016. In this his position, Rob leads technical staff at the ARM Data Center and collaborates with ARM staff at eight other national laboratories as well as scientists from other institutions who provide technical support for ARM instruments and associated data products.

Awards

Significant Event Award  for department of Energy, ARM archive support for DOE, LES ARM Symbiotic Simulation and Observation - Decemebr 2016 

Significant Event Award  for Department of Defense, operatioanlizing explosive safety and munitions risk management, as lead investigator - May 2011

Significant Event Award for the Department of Homeland Security, Regional Technology Integration Initiative Assessment, as the communications lead - September 2005

 

Projects

Atmospheric Radiation Mesurement Program for the Dpeartment of Energy

Southeastern Transporataion Corridor Pilot Program for the Department of Homeland Security

Regional Technology Integration Initiative for the Department of Homeland Security

 

Publications

Next-gen tools for big scientific data: ARM data center example: Conference Paper IEEE Xplore Dec 2016 Vol. 1 Issue 1, pages 4026-4028

HPC infrastructure to support the next-generation ARM facility data operations: Conference Paper 2016 IEEE International Conference on (Big Data) Dec 2016 ISBN 978-1-4673-9005-7, page 3968

 

 

 

Contact Information