Hi, I’m Matt!

I use data & technology to
create a love driven world

When I can’t solve a pressing problem with Duct-Tape or WD40, I use Python.

Automation Accepted 🦾

I was tasked to take a multi-thousand line codebase and have it tested for as many scenarios as possible everyday, each scenario taking hours if not days. To make matters worse, I had no access to the cloud, no (reasonably sized) storage solution, a limited list of approved software, and unreliable network connectivity between machines. The solution I engineered honors the CI/CD principals of tools like GitLab/GitHub & Dask within a framework I practically constructed myself using approved tools such as Python, Jupyter, & a moderately sized Cluster.

Spoiler Alert: The Data is Poor 🔥

My most memorable occasion of dealing with poor data was a dataset from Smart Phones. The data was not consistently collected, the labels were usually wrong, and there was great distrust in if the data is what it truly claims to be due to bugs in the application that collected it. Still we had to use that data as per the customer’s request, so I got to work making the best out of it. I created a data ingest pipeline that ingested live-streaming data from AWS, ran it through a battery of clean up & data verification tasks in Python, ensure the data remained anonymized, & then save it efficiently.

Delivery Day Detour 🚨

I came in as a brand new member of the team onto a new project and in little under 14 days disaster striked. On the day we were supposed to deliver results (and most of the team has long left for the night), I and my project lead realized the delivery script was buggy and the data could not be submitted. I quickly got to work, using Python + Pandas to jump in and create a script to re-process the gigabytes of data, leading to a successful delivery.

I sincerely believe in using technology & data to solve problems and transform our world more effectively. My entire journey has led me down this digital road into creating a more love driven world.


I invite you to scroll through this page to see what I’ve done and what we can do together.


Most Recent Degree

Academic History

Graduated from the Gloucester County Institute of Technology with a 3.99 GPA. In the National Honors Society & National Technical Honors Society. Head editor of the school newspaper. Took several college courses from Rowan College concurrently.

Coursework of Interest

  • Intro to Machine Learning
  • Python Data Analysis
  • Parallel Computing
  • Bioinformatics
  • Data Gathering & Warehousing
  • Advanced Data Science
  • Investigation of Machine Learning & Neural Network Algorithms
  • Programming & Problem Solving I & II
  • Modeling Ecological Networks I & II
  • Computer Science Modeling & Simulation
  • Computational Modeling
  • Environmental Modeling
  • Computer Networking Principles
  • Modern Fortran Programming
  • Calculus I-III
  • Discrete Mathematics
  • Linear Algebra
  • Numerical Analysis

Technical Skillset

Favorite Programming Languages
Python (7 Years)
MATLAB (5 Years)
C/C++ (3 Years)
R (2 Years)
Python Skills
  • Biology: Biopython

  • Data Storage: Pandas

  • Math: Numpy & Scipy

  • Machine Learning: Keras, Theano, Tensorflow, & Scikit-learn

  • Text: Beautiful Soup, Element Tree, & Nltk

  • Visualization: Bokeh & Matplotlib

  • Web: googleanalytics & requests

C++ Skills
  • GNU Scientific Library

  • Parallelization: Cuda & MPI

Operating Systems
  • Linux (since 2005)

  • macOS (since 2006)

  • Windows (since 1996)

Other Skills
  • Agile: Jira

  • Automation: Jenkins

  • Cloud Computing: AWS Lightsail & DigitalOcean

  • Databases: MySQL, ElasticSearch + Kibana, & SQLite

  • Remote Access: ssh, x2go

  • Version Control: ClearCase & Git

  • Terminal: Bash, Csh, & Tcsh

Technical Experiences

Engineer at Lockheed Martin ATL

Integrated System Works: Human Systems Autonomy
Cherry Hill, NJ; 2018-Present
Everyday, I perform these roles:
  • Created and tested a variety of Supervised Models in Python to predict how users would respond to a survey.
  • In three days, created a data ingestion and modeling processing pipeline in Python to predict results from a human sensor.
  • Performed data exploratory techniques to determine if there are any correlations and evaluate any potential biases.
  • Supported the deployment of an ElasticSearch cluster to support improve reliability.
  • Created processes to ingest data into Amazon S3, InfluxDB, and other sources with respect to modeling needs. These processes had to encounter data of various types, bad data, differing (and often, incorrect) timezones, and handling open-ended user responses in a less open-ended manner.
  • Made significant contributions to a data ingestion & modeling pipeline to extract data from AWS S3 and process + model it on AWS EC2. This pipeline was intentionally designed to be flexible and have a variety of ways to generate new features easily.
  • Created a wiki to help newer engineers understand the technical configuration in the lab and how to get onboarded as quickly as possible.

Engineer at Lockheed Martin RMS

Radar Systems Engineering: Modeling & Simulation
Moorestown, NJ; 2014-2018

Everyday, I perform these roles:
  • Utilized open source technologies and new methodologies to store & analyze terabytes worth of data, by cleaning up big data and storing it as efficiently as possible, with respect to current limitations
  • Supported the rollout of a neural network & machine learning stack on servers disconnected from the internet
  • Automated the generation and reporting of key performance metrics to leadership
  • Assisted development teams in radar system/subsystem design, development, modeling, simulation, integration, and testing
  • Implemented continuous integration testing + nightly automation testing to improve software stability and reliability.
  • Streamlined our workflow processes & scripts during code commits and testing
  • Led several Lunch & Learn courses about Python Scripting & Packages (Pandas, matplotlib, bokeh, etc.)
  • Created a variety of Python scripts & tools to automate several of the management support tasks that teams are responsible for
  • Increased team morale by introducing team social events and creating opportunities for the team to provide feedback anonymously
Stories from my experiences:

We wanted to exponentially increase our test case by x5, but due to business constraints, we wouldn’t get additional resources for several months. I took this opportunity to create innovative solutions in Python to summarize data, delete data, and act on that freed space which permitted us to reach our goal without those resources arriving in. This now gives us opportunity to expand in ways we have not consider when we do get those resources.

Due to inconsistent processes across many teams & departments, there isn’t a consistent way to log errors & warnings, let alone report on successes in the unified software. But, we still wanted a solution to summarize and report on all issues across all teams. I created an fast-running, yet in-depth, algorithm to parse gigabytes worth of text data to handle all of these gotchas which is still in use four years later.

Several teams requested access to a newer version of Python and neural network libraries, which is a complicated request due to levels of red tape and necessary reviews. I led this software installation process by proactively reaching out to key stakeholders and pushing the process forward, resulting in software that was installed quicker than what it would typically take.

Some of my Favorite Non-Commercial Projects

Email Me

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