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About Owen McGlynn
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About Owen McGlynn

Owen McGlynn profile picture

Hi there, and thanks for stopping by! My name is Owen and I'm a Computer Science and Mathematics dual major at UMass Amherst (graduating May 2027) with a passion for building innovative solutions. I specialize in full-stack development, data analysis, and AI/ML applications. In my free time, I enjoy bouldering, hiking, skateboarding, baking pastries, and working on cars.

Education & Certifications

Currently pursuing degrees in Computer Science and Mathematics and a Minor in Japanese at University of Massachusetts - Amherst (4.0 Major GPA, 3.99 Overall). Certified in CompTIA Security+ and CompTIA A+.

Professional Experience

Honeywell FM&T (05/2025 - 08/2025)

DoE Q-Level Clearance in progress

As an IT Intern II with the development team, I designed automated tools that identified over 1,900 deprecated program items and automated upgrade deployment for 40+ application servers, saving hours of manual work each month. I also led the recovery of a damaged server cluster—restoring operations in under a day—and presented integration strategies that were adopted by senior engineers.

Helzberg Diamonds (05/2024 - 08/2024)

Previously, at Helzberg Diamonds, I built a full-stack web app to automate CCPA compliance, decreasing processing time by 90%. I also developed backend automation with Snowflake and Jupyter, helping the company achieve near-total compliance and better manage customer data in general.

Certifications

CompTIA Security+ CompTIA A+

Leadership

Active in Cybersecurity Club, AI Club, and Rock Climbing Club (Setter/Organizer). Former Chef and Shift Lead managing teams of 5-8 staff.

Skills

Spoken Languages

English Japanese

Programming Languages

Java Python C SQL JavaScript/TypeScript Tcl/Tk MQL Bash

Tools & Platforms

Snowflake PostgreSQL Git Docker Linux VIM Unix Jupyter Notebooks

Libraries & Frameworks

React Node.js Pandas Streamlit PyTorch TensorFlow NumPy NLP

Contact Information

GitHub Profile LinkedIn Contact Info Download Resume
BetaBreak - Climbing Route Optimizer
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BetaBreak - Climbing Route Optimizer

An advanced climbing route optimization web application that uses A* pathfinding algorithms and biomechanical models to deliver real-time, personalized climbing recommendations.

This project actual began as a research paper for my Writing in Mathematics course. We were tasked with finding a problem in the real world that interested us and finding some way to apply our knowledge of mathematics to it. if you are interested in the full paper, you can find it here.

Key Features

• Advanced A* pathfinding algorithm with biomechanical modeling
• Real-time personalized climbing recommendations
• Interactive JavaScript frontend with computer vision backend
• ~95% hold-placement accuracy using computer vision
• Full-stack web application architecture

Tech Stack

Flask Python JavaScript CSS3 Computer Vision A* Algorithm
Still in progress, keeping code private
View Code
StorMe - Student Storage Platform
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StorMe - Student Storage Platform

A comprehensive web platform that enables students to rent local storage spaces during academic breaks. Built with modern full-stack technologies for scalability and security.

Key Features

• Web platform for students to find and rent storage spaces
• Secure backend API with robust authentication
• Advanced search functionality with location filtering
• Personalized user experiences and recommendations
• Docker containerization for easy deployment

Tech Stack

Node.js React Docker PostgreSQL TypeScript
View Code
Neural Text Generation RNN
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Neural Text Generation with Character-Level RNN

A deep learning project implementing a character-level Recurrent Neural Network for creative text generation, featuring manual hidden state propagation and advanced sampling techniques.

Key Features

• Character-level RNN with manual hidden state propagation
• Custom embedding layers for character representation
• Sliding-window dataset pipeline for efficient training
• Temperature-based sampling for creative text generation
• Hyperparameter tuning for coherent English generation from literary texts

Tech Stack

PyTorch NumPy NLP TensorFlow Matplotlib Python
View Code
Contact Owen McGlynn
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Get In Touch

I'd love to hear from you! Feel free to reach out about projects, collaborations, or just to say hello.

Other Ways to Reach Me

Direct Email LinkedIn GitHub
Quantum Crypto Research Paper
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Quantum Cryptography Research Paper

Summary

Quantum Computing and its Effect on Cryptography examines how emerging quantum technologies threaten current encryption systems.

The paper explains key quantum concepts like qubits and superposition, and how algorithms like Shor’s could break widely used methods such as RSA. It also highlights the urgent need for post-quantum cryptography, reviewing NIST’s newly approved standards designed to resist quantum attacks.

The paper concludes with a roadmap for transitioning to quantum-safe encryption before the anticipated arrival of “Q-day.”

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