Keita Teranishi
About Keita Teranishi
Keita Teranishi is a Principal Member of Technical Staff at Sandia National Laboratories, specializing in resilience and fault tolerance in parallel programming models.
Current Role at Sandia National Laboratories
Keita Teranishi serves as Principal Member of Technical Staff at Sandia National Laboratories in Livermore, CA. He has held this position since 2013. His work involves significant contributions to the field of resilience and fault tolerance in parallel programming models.
Previous Experience at Cray Inc.
Keita Teranishi worked as a Software Engineer at Cray Inc. from 2007 to 2013. During his 6-year tenure at the company, he contributed to software engineering projects in the Greater Minneapolis-St. Paul Area.
Educational Background in Computer Science
Keita Teranishi holds a Doctor of Philosophy (Ph.D.) in Computer Science from Penn State University, where he also earned a Master’s degree. In addition, he achieved a Bachelor's degree in Computer Science from the University of Tennessee, Knoxville. He has also completed a Technical Management Program at the University of California, Los Angeles in 2020.
Research Roles at Penn State University
During his academic career, Keita Teranishi served as a Postdoctoral Researcher and Graduate Research Assistant at Penn State University. His work from 2004 to 2007 and from 2000 to 2004 included significant research contributions in the field of computer science.
Mentoring and Leadership
Keita Teranishi has mentored a total of 11 student interns, which included 5 undergraduate students, 1 master's student, and 5 PhD students. His mentoring has contributed to the development of the next generation of professionals in the field.
Research and Development Contributions
Keita Teranishi has contributed to the development of high-performance parallel sparse tensor decomposition algorithms and software for multicore, manycore, and GPU platforms. He also served as Institutional Co-Principal Investigator of the ECP-xSDK project, which focuses on extreme scale scientific software development.