Hello! My name is Noah Burkhardt. I’m a soon-to-be graduate of the University of Maryland: College Park, studying Computer Science with a specialization in Data Science and a Minor in Mathematics. I’m passionate about Data Science, and hope to pursue a career in it in the future. Going hand-in-hand with this is my interest in Machine Learning and Artificial Intelligence, which I’ve had the privilege of exploring through several undergraduate classes and research opportunities.
My philosophy as a computer scientist is to be language-agnostic, choosing to focus on broadly understanding programming paradigms, rather than spending my time diving into a particular language or library. As a graduate of the ACES Honors College on campus, I am deeply familiar with modern cybersecurity concepts. And having three summer internships on record, I have the teamwork skills required to be a contributing member of an Agile development team.
In my free time, I enjoy running, hiking, and watching reruns of Psych. In fact, the photo above was taken on a hike in Acadia National Park! Check out my resume below, or keep scrolling to learn more about my professional qualifications…
GPA: 3.76
Minor in Mathematics
ACES Honors College
CMSC132 (Object-oriented Programming II)
CMSC216 (Introduction to Computer Systems)
CMSC250 (Discrete Structures)
CMSC330 (Organization of Programming Languages)
CMSC351 (Algorithms)
CMSC389W (Visualization through Mathematica)
CMSC421 (Artificial Intelligence)
CMSC426 (Computer Vision)
CMSC320 (Data Science)
CMSC422 (Machine Learning)
CMSC414 (Computer and Network Security)
CMSC456 (Cryptography)
CMSC420 (Advanced Data Structures)
CMSC412 (Operating Systems)
MATH140H (Honors Calculus I)
MATH141H (Honors Calculus II)
MATH240 (Introduction to Linear Algebra)
STAT400 (Applied Probability and Statistics I)
MATH241H (Honors Calculus III)
MATH401 (Applications of Linear Algebra)
MATH405 (Proving Linear Algebra)
MATH406 (Number Theory)
MATH463 (Complex Variables)
HACS100 (Foundations in Cybersecurity I)
HACS101 (Applied Cybersecurity I)
HACS200 (Applied Cybersecurity II)
HACS208E (Reverse Engineering)
HACS208Y (Cyber Psychology)
HACS287 (Undergraduate Research in Cybersecurity)
Designed and developed a game simulation tool loosely based on chess, then trained a reinforcement learning agent using Deep Q-learning and Actor Critic models. The trained agent performed 98% better than the control agent.
Used NLP methods such as sentiment analysis and TF-IDF to determine the similarity between song lyrics on the Billboard Top 100. Used the same methods to show that there is a positive correlation between profanity in music and popularity on platforms like Spotify.
Prototyped a blockchain-based voting system which exposed a REST API frontend to allow for easy interaction. Conducted a survey afterwards to determine favorability of this system over the current voting implementation.
Built a honeypot, which is an intentionally insecure web-facing server, and studied the correlation between "bot-like" actions and total intrusion time. Showed that bot intrusion time is significantly less than human intrusion time.
Conducted research on the use of biometric hand scanners at the University of Maryland dining halls, and created an informative video detailing the benefits and potential weaknesses of such a system.
Wrote scripts to automate several cloud provisioning processes, resulting in a 90% reduction in ticket backlog.
Summer 2019 — Developed a traffic generator for a network simulation tool, written in Python. Utilized Docker, Nginx, RabbitMQ, and scapy.
Summer 2018 — Developed and designed the user interface of a web-based HR solution written on a MariaDB/Django backend and a VueJS frontend.
Scheduled team members in positions, managed certain financial aspects of the store, handled guest feedback, and oversaw training for 25+ team members.