Poorya Piroozan - Learning
Learning
What I’ve learned so far.
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Education
Maharishi University of Management – Fairfield, Iowa
(2018 – 2020)
Key Courses:
- Machine Learning
- Big Data
- Parallel Programming
- Advanced Software Development
University of Applied Sciences Upper Austria, Hagenberg, Austria, 2013-2015
Key Courses:
- Artificial Intelligence
- Augmented reality, mobile games
- In-game technologies, game architecture, game production, game design
- Software design, Human-computer interaction, computer graphics
University of Applied Science and Technology, Tehran, Iran, 2007-2011
Key Courses:
- Software Engineering, Artificial Intelligence, Algorithm design, Operating systems
- Object oriented systems, Database Implementation
- Computer simulation, Computer graphics
- Computer architecture, Systems programming, Machine and Assembly language.
- Differential equations, Engineering statistics, Engineering math.
Experience
Senior Unity Developer
Working on the company’s proprietary augmented reality software used in military and police training. (under NDA)
Unity Developer / Software Engineer
Software Engineer /Unity Developer
Creative engineer
Java programmer
Freelancer
Web design, multimedia
Game programmer
Master Thesis
Adaptive AI in a co-located multiplayer gameMy thesis aimed to find an approach for building an adaptive artificial intelligence (AI) agent for a co-located game. Lack of any control over the players regarding their number, movement, speed, direction or orientation in co-located games is what brings up the challenges associated with making a smart, yet adaptive AI. A multiplayer game was made as part of the thesis, which is inspired by the 80’s game Pac-Man, but in this game, Pac-Man is played by AI and people play the ghosts in the physical space. The AI should be able to do pathfinding for eating the dots, have pursuit behaviors for chasing the players while they are moving, utilize evade algorithms to escape from the players, and also be able to make strategic decisions on when to switch behaviors. Above all, the AI should be adaptive, changing actions based on players’ engagements. The thesis explores different models and algorithms while building a flexible AI agent. The final game is tested with multiple test conditions, both with extreme players made in code and with simulated data gathered from real human players. The performance of the AI is then evaluated against several predefined criteria. A video from testing an earlier version of the game can be viewed in the front section.
I AM LEARNING
Currently I'm experimenting with augmented reality and retro video games.