Aspiring Software Engineer - CS, Mines 2025

Luke Vo

303-***-**** Denver, CO ****@*****.*** linkedin.com/in/ltv0 github.com/ltv0 ltv0.me EDUCATION

Colorado School of Mines: Bachelor’s Degree in Computer Science, August 2022 - December 2025 GPA: 3.516 PROFESSIONAL EXPERIENCE

Colorado School of Mines -Python Entry Level Teaching Assistant, August 2023 - December 2025

• Troubleshot software installation, environment configuration, and code-level bugs for over 50 students.

• Led technical support by diagnosing complex errors and teaching students advanced debugging workflows.

• Standardize troubleshooting strategies across course sections to ensure consistent and efficient problem resolution.

• Evaluated project functionality and provided actionable feedback to help students resolve recurring technical issues. A2Z AutoPaintSupplies -Data Consultant, October 2025 - Current

• Engineered a scalable inventory management system integrated with the Square API, automating real-time stock tracking and transaction processing across the store.

• Designed and executed a full product catalog migration into the Square ecosystem, ensuring data integrity and accurate schema mapping throughout the process.

PROJECTS

Cosmetic Safety Analysis & Risk Modeling -SQL, Python, Notebook

• Engineered an Automated Data Pipeline using SQL and Python to ingest and clean large datasets of consumer product safety records. This was used to transform raw, unstructured data into a queryable format, allowing for faster identification of regulatory compliance issues.

• Developed visualizations in Matplotlib to identify high-risk product categories and track the frequency of chemical reports.

• Performed Advanced Statistical Filtering and Trend Analysis to isolate discontinued products versus active market threats. This analysis was conducted to reduce "noise" in the supply chain data. Socio-Economic Factors & Crime in Denver Analysis - Jupyter Notebook

• Cleaned and processed city-wide crime and census datasets using Pandas and NumPy, to prepare structured, analysis-ready data from raw government records.

• Visualized correlations between income, demographics, and reported crime rates using Matplotlib to communicate findings clearly to a non-technical audience.

Fall 2024 Denver Crime Statistics Analysis - R Studio

• Collaborated in a four-person team to analyze 28 demographic and crime-related variables, to identify statistically significant patterns across the dataset.

• Examined relationships between crime rates and temporal factors such as time of day and seasonality, uncovering trends with actionable public safety implications.

Weather Report- BlasterHacks 2026 Game Jam Second Place Winner - ltv0.me/blaster-hack-commandline-game

• TypeScript — Used to write type-safe game logic with strict type checking enabled via npm run type-check

• @chenglou/pretext — Leveraged the trending pretext library to render ASCII-style text glyphs on HTML5 canvas without bitmap assets;

• Developed and submitted a complete MVP featuring survival mechanics, progressive difficulty, and ASCII visual rendering. Longhopes Donkey Shelter Paddock Mucking Robot 2025 - ROS, Python, C, Docker

• Built an autonomous paddock-cleaning robot in a 4-person team, inheriting and refactoring prior projects to unify system architecture.

• Developed a real-time computer vision pipeline to process high-frequency image data, using Python and ROS to transform raw sensor input into actionable navigational coordinates.

• Worked directly with the shelter client to ensure the system was practical for staff with no robotics background. Game Development Project: LEXiCon - Godot / Blender

• Co-developed a 3D puzzle and point-and-click game featuring monogram-based mechanics to unlock new areas.

• Implemented gameplay systems and collaborated on level design within a four-person development team.

• Applied Agile principles and completed iterative sprints with a four-person development team to deliver functional game builds on schedule throughout the semester.

Calendar Booking System with AI Event Parsing - Local LLM, Google Cloud API

• Natural Language Event Parser: Converts human-readable event descriptions into JSONs using local LLM (Ollama llama3.2).

• Google Calendar Integration: OAuth2 authentication with Google Calendar API v3 for automated event creation. Automated Voice AI Appointment Agent Vapi, Twilio, Make.com

• Built a voice interface using Vapi and Twilio to handle natural language appointment scheduling, reducing the need for manual receptionist intervention.

• Architected an automation workflow in Make.com to connect voice-to-text data with cloud services, ensuring communication between the AI agent and backend databases.

• Integrated Google Calendar API to automate event creation, resulting in a fully automated booking process for users.

• Built Webhook listeners to log structured call data into Google Sheets after each interaction, maintaining a record of client appointments. SKILLS

Programming Languages: Python (Pandas, NumPy, Matplotlib), SQL, R, Java, C/C++, OCaml, HTML/CSS. Data & Automation: ETL Pipelines, Data Wrangling, Schema Mapping, Vapi, Make.com, Twilio, Google Cloud API. Systems & Infrastructure: Docker, Linux/Unix, Shell Scripting (Makefiles), Git, RISC-V, Networking (TCP/IP). Specialized Frameworks: ROS, JupyterHub/Notebook, Godot, Unity, Local LLMs (Ollama), Flask, SQL Databases. Software Engineering: Agile/Scrum, Object-Oriented Programming (OOP), Data Validation, Technical Support.

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