Academic Work

Project F January 2021 - April 2021

Project F is a 2-player Platform-Fighter.

The game focuses on fast paced gameplay and features 2 playable characters: a melee focused adventurer, and a range focused archer.

Download via Google Drive

+ Additional Credits and Info

Copyright 2021 © DigiPen Institute of Technology
Art Credits
Equipment Pro (Font) - SomePx || UI Icons - Kadith || Peaceful Nightfield - Trixie || Winter Forest - Kauzz || Warped City - Ansimuz || Archer (Character Pack 4) - OcO || Pixel Adventurer - Rvros
Music Credits
DigiPen Sound Library || Sonniss GDC Audio Bundles 2018, 2019, & 2020 || Basic Implosion - KevinMacleod , License || Half Mystery - KevinMacleod , License || Danger Storm - KevinMacleod , License
Special Thanks
Rich Rowan, Devin Hentz, Cole Astaire, Max De Nadai, Alex Sirisuwan, Bryce Denmark, Hugo Anquier, Kyle Wood, Sau Ching Leung, Jirawat Jumponkunawut, Oliver Clubb, Kaitlyn Lee, Cass White, Shania Williams, Shane Staller, Crow Downey, Judd Jundi, Danny Jundi, Alex Winestock

(Side) Quest! January 2021 - April 2021

(Side) Quest! is an Adventure Platformer where the player experiences a day in the life of an ADHD addled Squire.

The game features a simple, yet intuitive player controller and is focused on selling the overloaded feeling that can come with ADHD, especially if there’s a lot on a person’s plate. The game uses various mechanics and UI effects to simulate the distracted nature and overwhelming thought patterns of an individual with ADHD.

Download via Google Drive

+ Additional Credits and Info

Copyright 2021 © DigiPen Institute of Technology
Art Credits
UI Icons - Kadith || Pixel Adventurer - Rvros
Music Credits
DigiPen Sound Library || Sonniss GDC Audio Bundles 2018, 2019, & 2020
Special Thanks
Eric Cagle, Ryan Woods, Hugo Anquier, Judd Jundi, Elgin Ciani, Danny Jundi, Eric Calabrese, Dillon Piette, Max DeNadai, Michael Crouch

Bubble Theory AI January 2021 - April 2021

BubbleTheoryBubbles — Bubble Theory is an unofficial theory that describes how some E-sports players analyze and manage the space between themselves and an opponent. Based around this theory, I built an AI system that tries to: understand the space between itself and the player, predict player actions, understand when a player is approaching or retreating, and respond to this in a player-like fashion, rather than using canned AI attacks/animations.

The attached PDF contains a more detailed explanation and implementation guide for a simple variation on Bubble Theory AI. A working demo is implemented into the (Side) Quest! project linked above. Note that this demo may include some bugs as academic projects are uploaded in the same state in which they were submitted to the institution.

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