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Matt Boubin

Data Science Fellow
New York City Data Science Academy - September 2021
M.S. Electrical Engineering
Miami University - December 2021
B.S. Electrical and Computer Engineering
Miami University - May 2018


Introduction

I am a current Masters' student a Miami University in Oxford, OH. My research focus is on signal processing of electromagnetic interference and the health monitoring of electrical systems. I am a recent graduate of the New York City Data Science Academy Fellowship Program where I applied data analysis principles to public data. I have three years in industry as a digital signal processing engineer and data engineer where I managed and executed on research and development contracts. My current intrests are developing ETL pipelines, and I am currently working on open source projects to help develop a mobile app with sound middleware practices.

Find Me

Email: bubbinmj7@gmail.com

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Professional Experience

Data Science Fellowship

New York City Data Science Academy - New York, New York

Jan 2021 - September 2021

  • Used R and Shiny visualization tools to develop an application analyze international economic data and provide recommendations for industry data collection, and provided suggestions to the OECD, and international government agency
  • Used Beautiful Soup and Scrapy to extract data from popular music vendors to analyze commerce trends, and provided suggestions to discogs for record sales.
  • Developed a machine learning model to make improvements to homes in order to increase their market value
  • Used Google Colab and YOLOv4 to classify crop field objects to improve existing precision agricultural image processing techniques for cropfield diagnostics

Data Engineer - Contractor

GE Appliances - Louisville, KY

July 2020 - April 2021

  • Developed prototypes of new appliance features including robotics, diagnostics, and data monitoring for one of the largest appliance manufacturers in the US
  • Used Support Vector Machines to diagnose known problems with appliance Electromagnetic interference generated by appliances to monitor appliance usage with 90% accuracy for known appliances
  • Contributed to three US patents held by GE Appliances, and presented insights to the CEO of GE Appliances quarterly

Electrical Engineer

D'Angelo Technologies - Dayton, Ohio

May 2018 - March 2020

  • Used machine learning algorithms to classify radio frequency signals for cabling diagnostics
  • Developed custom data visualization platform in Python to interpret sensor data
  • Wrote proposals to fund two R&D projects valued at $150,000 for the National Shipbuilding Research Program resulting in technology acquisition from shipyards and the US Navy
  • Implemented a data driven solution to shore power connector testing to replace existing, dangerous measurement protocol

Graduate Research Assitant

Miami University - Oxford, Ohio

January 2017 - May 2018

  • Developed machine learning diagnostic tools for the Miami University Power Electronics Laboratory
  • Contributed to a non invasive biomedical device prototype
  • Taught four undergraduate laboratory courses incluing Power Electronics, Embedded System Design, Computer Aided Experimentation, and Hardware Design
  • Published four peer reviewed papers

Information Technology Leadership Program - Intern

GE Aviation - Cincinnati, Ohio

May 2015 - August 2015

  • Developed a middleware dashboard to display server performance metrics to the middleware diagnostics team using SQL and C#
  • Helped to develop a strategy to prevent critical server outages that cost the business 5 Million dollars per hour

Research Intern

AFIT Autonomy and Navigation Technology Laboratory - WPAFB, Ohio

May 2014 - August 2014

  • Parsed UAV flight test data using Robot Operating System (ROS) and C++
  • Configured gyroscope sensors for UAV flight tests