Machine Learning & Artificial Intelligence

The objective of this project is to teach the computer to make a prediction of what furniture should be specified to furnish a space, using prior furnished Revit models as the learning data. I implemented this MachineLearning application into lunchbox grasshopper plugin as a part of my internship with proving ground.

The main concept of this project is to have a co-creative drawing agent that collaborates with human users in real time artistic collaboration, using the user's facial gestures as input.

NBA teams win or lose games based on the number of win shares their players create. Being able to predict the career performance of a player in their rookie season is important to team management because it allows them to make better draft, trade, and personnel decisions to give their organization the best opportunity of winning a championship.

This study proposes using Interactive Genetic Algorithms for developing a fashion design aid system.