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Hi, I'm Nick.


I’m Nicholas Landry, a graduate student studying Computer Science at Colorado School of Mines. My interestes include scalable systems, machine learning/data science, and data-driven software development.


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Resume

Education

MS Computer Science, Colorado School of Mines

Aug 2025 – Present

Coursework: Advanced Algorithms, Advanced Databases, Theory of Computation

BS Computer Science, Colorado School of Mines

Aug 2022 – May 2025

GPA: 3.73 - Coursework: Operating Systems, Algorithms, Programming Languages, Database Management

Work Experience

Software Engineer Intern, Allegion – Golden, CO

Aug 2025 – Present
  • Simulate traffic of thousands of real-time connected devices and measure system performance using Locust (Python) testing to provide metrics on the platform’s ability to scale towards growth goals.
  • Analyze and validate simulated commissioning of thousands of devices by measuring query performance with PostgreSQL and using REST APIs to mimic real-time device actions, ensuring successful device setup.

Software Systems Engineer Intern, Allegion – Golden, CO

May 2025 – Aug 2025
  • Mapped subsystem interactions expressed in Microsoft Digital Twin Definition Language (DTDL) and TypeScript, creating a comprehensive reference of platform communication for the System Test team.
  • Collaborated with verification engineers to formally capture and ensure validation of system functionality by developing software requirements
  • Extracted key corresponding information between two subsystems by evaluating and cross-referencing Cucumber (Gherkin) tests, ultimately identifying gaps and ensuring consistency between tests.

Undergraduate Scientific Programmer, Payne Institute for Public Policy

September 2024 – May 2025
  • Developed and implemented machine learning models for classification of global high-temperature sources, including You Only Look Once (YOLO) for image classification and Support Vector Machines (SVM) to improve geospatial analysis accuracy and automation.
  • Contributed to a multiyear catalog of oil and gas flare detections by preprocessing hundreds of thousands of satellite images via Google Earth Engine and applying AI predictive models, including the Google Gemini API, for classification

Projects

Analysis of LLM’s Adherence to Secure Software Development Best Practices

Collaborated with a team to analyze code generated by LLMs for software-security best practices using NLP and ML techniques.

Classifying Global High-Temperature Emission Sources with Computer Vision

Built a pipeline to classify satellite-detected hotspots using AI, computer vision, and Google APIs for real-time analysis.