Eric Goodman
About Eric Goodman
Eric Goodman is a Principal Member Technical Staff at Sandia National Laboratories with a Ph.D. in Computer Science from the University of Colorado at Boulder. He has developed high-level languages for streaming graphs, converted natural language queries into SQL, and contributed to scalable computing and anomaly detection in cyber-related datasets.
Company
Eric Goodman is currently working at Sandia National Laboratories as a Principal Member of Technical Staff. He has been with the organization since 2005, contributing his extensive knowledge and expertise in various complex technical projects. Sandia National Laboratories focuses on developing science and technology to solve national security issues.
Title
Eric Goodman holds the title of Principal Member Technical Staff at Sandia National Laboratories. In this capacity, he engages in high-level technical projects, advanced research, and innovative development. His role demands strong analytical skills and deep knowledge of computer science and related fields.
Education and Expertise
Eric Goodman earned his Doctor of Philosophy (Ph.D.) in Computer Science from the University of Colorado at Boulder, studying from 2012 to 2019. He also holds a Master of Science (MS) in Computer Science from Brigham Young University, completed between 2003 and 2005. Additionally, he has a Bachelor's degree in both Computer Science and Mathematics from Brigham Young University, where he studied from 1999 to 2003.
Research and Development
Eric Goodman has made significant contributions in several areas of research and development. He developed a high-level language for expressing queries on streaming graphs, translating them into Scala code executed on Spark. He also created methods for converting natural language queries into SQL statements using combinatory categorical grammar (CCG). His anomaly detection approach increased the AUC for the receiver operating characteristic by up to 27.5% on cyber-related datasets.
Technical Projects and Publications
Eric Goodman has led and contributed to several key technical projects. He ported graph-analysis codes from the Cray XMT supercomputer to the SGI Ultraviolet, developed scalable hashing strategies for power-law distributed data, and published results in Supercomputing. He also created a scalable semantic web query and inferencing engine on shared memory supercomputers, scaling up to 512 processors, and developed a MapReduce infrastructure for the Cray XMT. Additionally, he contributed to modeling expert and novice behavior for automated assessment technologies in support of training Navy personnel for the Office of Naval Research.