Keith Moore earned a BS in mechanical engineering from the University of Tennessee. He specializes in applying advanced data science and natural language processing algorithms to complex data sets and is responsible for IoT and algorithmic product development at SparkCognition.
Leadership: Moore began his career at National Instruments as an analog-to-digital converter and vibration software product manager. Prior to that, he developed client software solutions for major oil and gas, aerospace, and semiconductor organizations and was responsible for the growth and development of data acquisition products. He joined SparkCognition in Austin as a senior product manager working with a dedicated team of developers and data scientists to create algorithms that are applied to the fields of asset monitoring, financial modeling, and cyber security.
As a leader in this discipline, Moore has worked closely with leadership teams at Fortune 50 companies and using the information gathered to create roadmaps for development for both prognostics (SparkPredict) and automated model building (Darwin) products with the goal of using Big Data to solve problems within industry.
From a technology standpoint, this involves complex algorithm development with a data science team, maintenance infrastructure integration with historian systems, sensor-based pattern detection, and natural language processing.
Accomplishments: Moore is helping to reimagine industrial maintenance for optimized asset management. He is an expert in this technology, which analyzes sensor data and uses machine learning to return actionable insights, flagging suboptimal operations and identifying impending failures before they occur. In his leadership role, Moore is identifying creative algorithmic ways to revolutionize maintenance by minimizing downtime and delivering millions of dollars of savings in operating costs.
Moore also has been instrumental in introducing companies to the Darwin automated model building solution offered by SparkCognition. This allows customers to move from data to an accurate model in less time than traditional methods, enabling the rapid prototyping of scenarios and productive extraction of insights. Moore’s work in this space also enables teams to rapidly deploy machine learning models into their applications to drive business value in an adaptive, repeatable way.
Perspective: “I’m incredibly happy and humbled to be a part of the SparkCognition journey and team as we continue to drive global value through AI solutions and collaborate with our partners and academia to advance the science of AI.”