Elkin Garcia
About Elkin Garcia
Elkin Garcia is a Principal Firmware Systems Architect at Synaptics Incorporated, where he has worked since 2014. He holds a Master's Degree in Electrical and Computer Engineering from Universidad de Los Andes and a Ph.D. from the University of Delaware, with a strong focus on parallel computing and machine learning.
Current Role at Synaptics
Elkin Garcia serves as the Principal Firmware Systems Architect at Synaptics Incorporated. He has held this position since 2014, contributing to the company's initiatives in the San Francisco Bay Area. His role involves overseeing the design and development of firmware systems, with a focus on performance and energy optimization.
Educational Background
Elkin Garcia completed his Bachelor’s Degree in Electrical Engineering at Pontificia Universidad Javeriana from 1998 to 2003. He then pursued a Master’s Degree in Electrical and Computer Engineering at Universidad de Los Andes from 2004 to 2006. Furthering his education, he obtained a Doctor of Philosophy (Ph.D.) in Electrical and Computer Engineering from the University of Delaware, studying there from 2009 to 2014.
Previous Work Experience
Prior to his current role, Elkin Garcia gained diverse experience in various positions. He worked as a Graduate Intern in Parallel Systems at Intel Corporation for three months in 2014. He also held an Intern Software Engineer position at Intel Corporation from 2011 to 2012. Additionally, he served as a Research Assistant at the University of Delaware from 2008 to 2014, and worked as an Instructor at Universidad de Los Andes from 2004 to 2008.
Teaching Experience
Elkin Garcia has a background in academia, having served as an Instructor at Universidad de Los Andes from 2004 to 2008. He also held positions as an Adjunct Professor at Pontificia Universidad Javeriana from 2003 to 2006 and as a Teaching Assistant from 2000 to 2002. His teaching experience spans various aspects of electrical engineering and computer science.
Areas of Expertise
Elkin Garcia possesses expertise in several technical areas, including parallel computing and machine learning. He has extensive experience in scalability and numerical algorithms, focusing on the design and development of concurrent algorithms. His specialization includes multi-threaded languages, signal processing, and compilers, emphasizing performance and energy optimizations.