About Me
Doug LaMaster has established himself as a versatile engineering professional with a profound expertise in a wide range of fields, including machine learning, programming, cryptography, electrical testing, embedded systems, finite element analysis, and more.
Throughout his career, Doug has demonstrated a consistent track record of innovation and problem-solving. At Leidos, he leverages GPS technologies to explore new applications across various domains. Previously, at Riverside Research, he worked with AFRL (Air Force Research Lab) to develop cutting-edge machine learning algorithms to perform side-channel analysis. During his time at PreTalen, he excelled as a PNT engineer, becoming a subject matter expert on inertial systems and sensors. He also worked at Intel processing millions of dollars worth of product weekly.
But his passion right now is in using automation and machine learning to help people.
Contact Details
Doug LaMaster
(928) 362-0986
doug@douglamaster.com
Education
Northern Arizona University
Master of Science in Mechanical Engineering • May 2024
Completed thesis and published papers on a novel thermodynamic model to predict the response of a magnetic shape memory alloy (MSMA) to magneto-mechanical loading.
Northern Arizona University
B.S. Mechanical Engineering • May 2012
Completed studies in Mechanical Engineering with an emphasis in solid mechanics and heavey extracurricular work in electronics. Researched, characterized, and manufactured structural super capacitors.
Northern Arizona University
B.S. Mathematics • May 2012
Completed studies in Mathematics. Emphasis in applied Mathematics.
Work
Leidos
PNT Engineer • June 2023 - Present
As a Position, Navigation, and Timing Engineer at Leidos, I have been responsible for determining methods to use GPS both defensively and offensively. Automated pipelines to allow for faster experimentation.
Riverside Research
Senior Research Engineer • August 2018 - June 2023
As a senior research engineer, I work to develop the tools to perform the data analysis to evaluate micro-electronics. Assessment involves development of machine learning algorithms for classification and evaluation. Experimented with Convolutional Neural Networks, Data analytics, pre-processing techniques, classification, data pipelines, and statistical models.
PreTalen
PNT Engineer • March 2017 - August 2018
As a Position, Navigation, and Timing engineer, I have become the subject matter expert for inertial systems and sensors at PreTalen.
Intel
Process Engineer • March 2016 - March 2017
As a process engineer and tool-owner in the high-volume manufacture of computer chips, I was responsible for keeping production running at full capacity. Within months, I became the primary point of contact for a fleet of lithography machines processing approximately $1.2B worth of product weekly.
Skills
My education in mechanical engineering and mathematics gave me a broad set of interests and experiences to draw from. The field I am most passionate about right now is AI.
Testimonials
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