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Alex Berrian has worked in various roles since 2007. From 2007-2009, they worked as a Programmer at Advanced Ion Beam Technology, where they designed a program in C to direct operations of a silicon-wafer ion implantation machine. From 2009-2011, they worked as a Grader at Tufts University. From 2011-2012, they worked as a Graduate Teaching Assistant at The University of Iowa, where they instructed two discussion sections per semester and led interactive in-class exercises in Mathematica. From 2012-2018, they worked as a Graduate Student Researcher at UC Davis, where they conducted research in audio signal processing and applied harmonic analysis. From 2015-2016, they worked as a Summer Research Intern at Smule, Inc., where they worked on acoustic feedback detection and automatic classification of audio recordings based on their vocal and instrumental content. From 2018-2021, they worked as an Audio Research Engineer at Gracenote. Since 2021, they have worked as an Audio Research Engineer at DSP Concepts.

Alex Berrian's education history includes a Doctor of Philosophy (Ph.D.) in Applied Mathematics from the University of California, Davis from 2012 to 2018, a Master's Degree in Mathematics (Concentration in Applied Mathematics) from the University of Iowa from 2010 to 2012, a Bachelor's Degree in Mathematics from Tufts University from 2006 to 2010, a Study Abroad program in French Language and Literature from the Center for University Programs Abroad in 2009, and a Study Abroad program in Japanese Language and Literature from Kansai Gaidai University in 2008. Additionally, Alex Berrian has obtained certifications in Convolutional Neural Networks, Deep Learning Specialization, Sequence Models, Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization, Neural Networks and Deep Learning, Structuring Machine Learning Projects, Machine Learning, and Audio Signal Processing for Music Applications from Coursera between 2020 and 2015.