Every semester, we collaborate with industry clients as well as tackle interesting problems on our own.
Experiment on multi-agent reinforcement learning for playing the popular sport, soccer
Apply Computer Vision techniques to improve tiny object detection on measuring roof debris and damage
Build an encoder for images that can perform few-shot training across CV tasks using unsupervised learning
Explore adversarial models to track sleep stages by comparing results from watch and radio frequency data to brain wave data
Develop a profitable trading strategy for the market today based on common technical indicators
Create an AI web app using Monte Carlo sampling, deep and reinforcement learning to play heads up and nine handed no-limit Texas Hold'em poker