Mark Frank

Mark Frank has extensive work experience as a Principal Engineer in various companies. Mark started their career at Skyworks Solutions, Inc. in 1999, where they led a team of 12 engineers and was responsible for project planning, software architecture, system simulation, and automated testing for a GSM/EDGE baseband processor. From 2005 to 2008, Mark worked at Raytheon Missile Systems as a Principal Engineer, leading a group of 8 engineers and developing new waveforms for missile radar systems. Mark also served as a project engineer for advanced radar seeker and was involved in DARPA programs. At Rohde & Schwarz, Mark was a Principal Engineer from 2008 to 2018, leading embedded software development projects for spectrum and network analyzer platforms. Mark optimized measurement routines for speed and accuracy. Mark then joined Sandia National Laboratories in 2018 as a Principal Engineer, specializing in signal processing. There, they developed FPGA and embedded software solutions for radar and communication applications and designed compression software for a radio telecom application. Currently, Mark works at AMERGINT Technologies as a Principal Engineer, implementing software radio functions on Nvidia GPUs and designing test frameworks for radio functions.

Mark Frank has a strong education background in the field of Electrical and Electronics Engineering. Mark obtained a Bachelor of Science (BS) degree in Electrical and Electronics Engineering from the University of Colorado Boulder. Subsequently, they pursued further education at Clarkson University and Arizona State University, where they focused on Electrical and Electronics Engineering. Mark completed their doctoral studies and earned a Doctor of Philosophy (Ph.D.) degree from Arizona State University.

Additionally, Mark has obtained several certifications to enhance their knowledge and skills in the field. Mark completed various courses and certifications, including the Deep Learning Specialization, Convolutional Neural Networks, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, and Structuring Machine Learning Projects. These certifications were obtained from Coursera. Furthermore, they have also acquired certifications in Big Data Foundations from IBM.

Mark also possesses certificates in Machine Learning and Neural Networks and Deep Learning from Coursera Course Certificates, although the specific completion dates are not provided.