Name: Thomas Galati
1. What is your current position?
I am currently a Game Data Analyst at Gameloft.
2. What role did you play at UXR Lab?
I was a Grad Student working on my Masters degree in Computer Science. I assisted in research by helping run studies and writing in papers.
3. What inspired you to go into games and UX?
As early as I can remember I have always had a passion for games, so it was only natural for me to gravitate towards learning the development process behind the scenes. It wasn’t until much later on, after I discovered a love of fighting games, that I realized how much I enjoyed breaking down and anticipating user behaviours. From there, I saw that I could use this to help me in game design, and found that I enjoyed looking at the “big picture” of this data.
4. What are some games and apps whose design you love? Why is that?
Gameplay-wise, I like games that reward pattern recognition, like puzzle games or fighting games. I also like games that have major decisions, and have the capacity to show the decisions that other players made. Examples of this are Life Is Strange and Fire Emblem: Three Houses, which show you which percentage of players took a given action. I always like it when I get to see a slice of data in games.
5. How did you get to join UXR Lab?
In my final year of Undergrad, instead of a capstone project, I was offered an opportunity to work on the Vixen project as part of an entrepreneurship incubator. The Vixen project is a data visualization tool started in what is now the UXR Lab; it is a Unity3D plugin that would help automate the logging of game telemetry data in Unity (this was before Unity Analytics). I decided that, instead of continuing the business concept after graduation, I wanted to expand my knowledge of data analytics. Fortunately, Dr. Pejman Mirza-Babaei had an opening for a Grad Student, and so I was able to pursue my research.
6. What is your favorite project that you have worked on?
My favourite project I have worked on is a tool that scrubs gameplay footage and draws game telemetry from it. My proof of concept was a python script that processed pre-recorded gameplay of a fighting game, Ultra Street Fighter IV. I used it to determine the health and special meter remaining of a given contestant at any given moment in the gameplay. This tool allows for gathering telemetry in a game without source code access, after the gameplay occurred. It could be used to automate the processing of large amounts of video, which may be invaluable for certain research projects.
7. If you could give any advice to the future UXR Lab members, what would it be?
Don’t just read papers, make sure you take the time to actually understand them. When working on your own projects, ask for feedback early, and ask for feedback often. When you’re deep in your own ideas, you might miss something simple that someone else may be able to point out.
8. What are some of your favorite aspects of UXR Lab?
The collaborative environment was probably my favourite aspect. Everyone is willing to work together and assist in any way they can, and all are willing to give feedback on given ideas. Each different perspective can bring value.