About Me
Hello, my name is Matthew Amato-Yarbrough, and I’m a full-time graduate student at Northern Arizona University studying for a Master of Science in Computer Science.
My interest lies in designing software architectures for complex systems that tackle unique and challenging problems, while utilizing high-performance computing, machine learning, and Bayesian statistics. I have an intermediate understanding of C/C++ and Python, as well as a functional to intermediate understanding of MATLAB and R.
Projects
C++, Python, ROS 2, MAVLink
• Create a system for monitoring wildlife radio tags on limited hardware to detect and track emitted pulses.
• Establish and monitor a UDP or serial connection with a PX4 autopilot for telemetry collection.
• Encode and decode MAVLink messages that are sent between the computer’s PX4 autopilot and GCS’s PX4 autopilot via SiK 915 MHz telemetry radios.
• Enacting user commands onto multiple low-level processes, monitoring the status of those processes, and summarizing information for user access.
• The repositories that contain the code for this iteration of the project are currently private. They will be made public at the end of my thesis. I will also post a copy of my thesis here once I have completed my thesis defence.
External C++ Functionality in CmdStan
https://github.com/matthew-ay/external_cpp_functionality_in_cmdstanAugust 2022 – January 2023
C++, CmdStan, Bayesian Statistics
• The project produced a guide for integrating external C++ code into Stan models using CmdStan.
• Generated C++ files, Stan models, terminal output, and make files to serve as reference materials for users following the walk-through.
Licht-cpp (NLM Module)
www.ceias.nau.edu/capstone/projects/CS/2020/Andromeda-S20August 2019 – August 2020
C++, CMake, GoogleTest, Gnuplot
• A module that quickly approximates parameter estimates for predicted and observed light curve data using a C++ implementation of the Nelder-Mead method.
• Please refer to the NLM sections of our team’s final report for a detailed explanation of the NLM module.
• The repository that contains the code for the NLM module is currently private.
Experience
NAU - School of Informatics, Computing, and Cyber Systems
nau.edu/school-of-informatics-computing-and-cyber-systemsGraduate Research and Teaching Assistant
April 2021 – May 2023
• Design and develop software for signal processing, data analysis, network and peripheral communication, and process management in an NSF-sponsored project.
• Conduct thesis research and development on the UAV-RT project with guidance from my faculty advisor and the co-principal investigator, Dr. Paul Flikkema, and oversight from the principal investigator, Dr. Michael Shafer.
• Teach CS 122, 126, and 136 lab sections, including presenting weekly labs, grading student work, holding office hours, communicating with students, and attending GTA meetings.
Lowell Observatory
lowell.eduUndergraduate Software Developer (Capstone and Internship)
August 2019 – August 2020
• Developed a Non-linear Minimizing (NLM) module using a C++ implementation of the Nelder-Mead method to approximate parameter data for one or more observed light curves.
• Communicated weekly via email and video conferencing for status updates and feedback on future enhancements.
• Collaborated with team members on implementing multiple modules concurrently in an existing codebase.
NAU ITS Classroom Support
in.nau.edu/its/classroom-supportStudent Technician
August 2016 – September 2018
• Setting up and configuring classroom technology, including projectors, sound systems, computers, and other devices.
• Training faculty and staff on how to use classroom technology effectively.
• Providing technical support to faculty and students using classroom technology.
• Assisting with the design and implementation of new technology initiatives in classrooms.
• Documenting and tracking technical issues and solutions to facilitate continuous improvement.
Education
Northern Arizona University
nau.edu/school-of-informatics-computing-and-cyber-systems/Master of Science in Computer Science, GPA - 3.50
August 2021 - December 2023
As a graduate student at NAU, I had the opportunity to work on thesis research and software development, allowing me to gain a comprehensive understanding of signal processing, data processing and analysis, network and peripheral communication, and process management.
Through my statistics and data science courses, I gained extensive knowledge in Bayesian statistics, which enabled me to develop a deep understanding of the principles and applications of statistical inference. Additionally, I acquired expertise in data science and analysis, including the use of various tools and techniques for data analysis.
I gained experience in shared and distributed programming, enabling me to design and implement complex software architectures within the realm of high performance computing. Finally, I deepened my understanding of computer architecture, allowing me to optimize software performance and better understand the underlying hardware.
All of these skills and knowledge were acquired during my time as a graduate student at NAU, and have prepared me well for a career in the field of computer science.
Languages/libraries used: C/C++, Python, R, MATLAB, Stan, JAGS, OpenMP, and MPI.
Relevant Courses:
• INF 504 - Data Mining and Machine Learning
• INF 511 - Modern Regression I
• INF 512 - Modern Regression II
• EE 514 - Computer Architecture
• CS 550 - Introduction to Parallel Programming
• CS 552 - High Performance Computing
• CS 626 and 626L - Applied Bayesian Modeling and Lab (Sit in)
• CS 685 - Graduate Research - External C++ Functionality in CmdStan
• CS 697 - Independent Study - Digital Signal Processing
• CS 699 - Thesis - UAV-RT Project
Northern Arizona University
nau.edu/school-of-informatics-computing-and-cyber-systems/Bachelor of Science in Computer Science, GPA - 3.30
August 2016 - May 2021
Throughout my undergraduate years at NAU, I was able to work on a variety of computer science projects spanning different courses. These projects were completed using programming languages like C, C++, Java, Python, R, HTML, JavaScript, CSS, Assembly, SQL, and Dart. Working on these projects, either alone or in a team, allowed me to not only broaden my understanding of computer architecture, but also solidify my enthusiasm for computer science and related topics.
Relevant Courses:
• MAT 136 - Calculus 1
• MAT 137 - Calculus 2
• MAT 316 - Introduction to Linear Algebra
• CENE 225 - Engineering Analysis
• CS 249 - Data Structures
• CS 315 - Automata Theory
• CS 345 - Principles of Database System
• CS 386 - Software Engineering
• CS 396 - Principles of Languages
• CS 399 - Mobile Application Development
• CS 421 - Algorithms
• CS 451 - Mechanized Reasoning
• CS 460 - Computer Networks
• CS 480 - Operating Systems
• CS 476 & CS 486 - Capstone
• CS 499 - Advanced Mobile Development
Downloadable Resume
For a downloadable PDF version of my resume, please click here.