This project was a collaboration between the Computer Science departments of UMASS Boston, and the Beijing Institute of Technology. We proprosed the idea that traditional methods of training for earthquake safety were inefficient, and inadequate, and that a virtual training drill would better. We implemented an earthquake simulation, using real data from an actual quake, using Unity, and used the HTC Vive as our virtual reality headset for the training and drills. In the end, our user study generated empirical evidence supporting our hypothesis.
Accepted to IEEE Transactions on Visualization and Computer Graphics (TVCG) and published in (Special Issue on IEEE Virtual Reality 2017).
Grind for Levels is a small game completed as part of a Weekly Game Jam challenge. The theme of the contest was "Obey," and my interpretation of that theme led me to create a tiny-scale turn based strategy game. Because of the contest's time constraints, there isn't a great deal of content, but I tried to make the game into as much of a polished prototype as I could, in the time I had available. This project was conceived in roughly 45 hours of work.
Divining Top is a Magic the Gathering card database and thesaurus tool for the Android platform. It allows the user to search for cards by name, type, or text. It also allows the user to find cards similar to the one he or she is looking at. This utilizes a search algorithm based on weighted keywords and key-phrases.
Alchemy Toolkit is a tool that I created in order to make development of my game, Alchemy and Artifice, easier. The toolkit takes advantage of the fact that the game is largely data-driven, and provides a GUI interface for editing all of the game's enemies, items, and skills, as well as all of the game's dialogue.
The built-in script editor can convert scripts (written in a custom scripting language devised for this project), to byte code, which can be executed in-game. A.I. scripts can be attached to monsters, while unique effects can be attached to items and skills.
This project was a collaboration between the UMB Computer Science Department and the Boston City Police Department. Unfortunately, I'm not at liberty to disclose the data itself, but the project entailed using machine learning and data mining techniques to analyze crime data, as well as the geometric data for the city itself, in order to identify patterns.
Machine learning techniques utilized include linear and logistic regression, k-means clustering, and gradient descent. Visualization of data was done in PyLab using matplotlib.
FourBlog is a lightweight blogging platform. A very lightweight blogging platform. Not counting the included .CSS layout file and documentation, it's less than 4kb. I had fun with the idea of making it as small as possible, while still having clean code, and a slim-but-pragmatic API. It's key points of attraction are its flexibility with fitting into a website layout, and that its appearance is completely customizable through a single, simple .CSS file. This website uses it, so you can see it in action.It is provided under the MIT license.