

About Me
Hi there, I'm Tyler. I've been tinkering with computers and programs since I was 12. Coding became a real passion for me back in 2019 when I started creating mods and collaborating with teams for the game Arma 3. These days, I spend my time working on mods for Arma Reforger and whipping up basic Python scripts. I'm certified in C++, C#, and SQL, and I'm pretty handy with Python and SQF too. Just your average tech enthusiast trying to make cool stuff!
Arma 3 New Vegas


Projects
Arma 3 New Vegas was a server with over 300+ players. I was the lead developer on this project, we ended up providing a unique experience not seen before in Arma 3 using the aftermath mod. Using the Altis Life framework I was able to store player data in an SQL database, create an engaging role-play experience, and have multiple factions, preset, and player-created factions that created a dynamic experience only we could provide.
Password Generator
I've made a password generator using TRNG and Python to make custom passwords for myself. After the password is created it automatically emails me the new passwords list in a password encrypted archive.
File Organizer
I've made a file organizer for my computer that runs in the background using a Windows task scheduler. It's made in Python and uses a dictionary to keep track of file names and their locations.
Playlist Downloader
I've made a Python script that uses a CLI to download YouTube videos and playlists to my computer. I use this for car rides to listen to podcasts going through areas with no signal.
Tik Tak Toe
My first project outside of Arma 3 and Arma Reforger was a basic game of Tik Tak Toe using a CLI. It was made in C++ and consists of the best of three rulesets. It has changing player sides, uses numpad inputs and stores wins and losses.


Coalition Lobby
Engineered an optimized lobby and server architecture in the Enfusion engine using Enforce Script, a C#-adjacent language, to reduce overhead and enhance performance. Integrated modular custom systems directly into the core gamemode, enabling reliable support for 128-player sessions. Features include dynamically generated faction ORBATs, a player-driven slotting system, and structured game phases—briefing, slotting, gameplay, and AAR—designed to streamline setup and coordination for large-scale multiplayer scenarios.


Coalition Gear Script
Co-developed a dynamic gear and loadout system that streamlines faction creation by using structured config files, reducing setup time from hours to minutes. The system enables full customization of uniforms, weapons, attachments, and equipment, down to the individual role level. This significantly improved workflow efficiency and allowed mission designers to rapidly build and scale complete, consistent factions for large-scale scenarios.
Drone Framework
Developed a realistic drone framework incorporating real-world systems such as line-of-sight-based signal strength, terrain-aware interference, signal jamming, and automatic reconnection logic. Implemented dynamic targeting data for recon drones and custom HUDs that simulate DJI and FPV drone interfaces. The jamming system accurately models real-world behavior—interfering with signal strength rather than outright blocking it—allowing operators closer to their drones than a jammer to maintain control.

Developed a Call for Fire training system in the Enfusion Engine using Enforce Script, a C#-adjacent language, to train the troop in artillery call-in procedures. The tool simulates realistic GM angles and target data acquisition, enabling accurate practice without the need for a physical simulation classroom, greatly improving accessibility and training efficiency.


Call For Fire Trainer


Land Nav Trainer
Built a land navigation trainer in the Enfusion Engine to train the troop using video game environments as a medium. The system enables dynamic generation of randomized navigation points from a preset pool and simulates GM angle for realistic terrain-based training. It provides a scalable, efficient alternative to physical land nav exercises, eliminating the need to reserve or prepare real-world terrain.