Matt Robinson started their work experience in 2003 at RedShift Company as a Research Scientist in Digital Signal Processing. Matt conducted experiments and investigations resulting in four patents and worked on various implementations including speech encoding, text-to-speech, hearing aids, and phoneme recognition. In 2013, they transitioned to the role of Machine Learning Software Developer - Speech Recognition, where they designed and implemented RedShift's backend speech recognition engine. Matt outperformed Google ASR on an ordering-specific test set and improved user experience by modeling ASR hypothesis confidence. In 2017, Matt joined Red Shift Voice Technology as a Senior Artificial Intelligence Engineer, where they oversaw the voice layer for online ordering applications and built RESTful integrations with third parties. Matt later joined Rendered.ai in 2021 as a Senior Software Engineer, where they built tools for image and video generation and analytics. Matt recently became a Lead Solution Architect, working with businesses to implement custom Rendered.ai Channels and generate useful data.
Matt Robinson has a strong educational background in physics, mathematics, and philosophy. Matt obtained a Master's degree in Physics from the University of Maine, where they studied from 2000 to 2003. Prior to that, they completed their Bachelor of Science (BS) and Bachelor of Arts (BA) degrees at the University of Nevada, Reno from 1993 to 1999, majoring in Mathematics and Physics and Philosophy respectively.
In addition to their formal education, Matt has also pursued further certifications to enhance their expertise in the field. Matt completed the "Mathematics for Machine Learning Specialization" and the "Natural Language Processing Specialization" from Coursera in February 2021 and January 2021 respectively. Matt also obtained the "Google Cloud Platform Big Data and Machine Learning Fundamentals" certification in May 2017 and the "Machine Learning" certification in March 2017, both from Coursera. These certifications demonstrate their ongoing commitment to improving their skills and knowledge in the areas of machine learning and data analysis.
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