I am a passionate AI researcher who lives at the intersection of CS, math, and statistics. I love to tinker and prototype new ideas. I work in everything from autonomous drone computer vision to large scale data pipelines/ML.
Currently researching the combination of control theory and reinforcement learning. In addition looking at choosing decision policies over adaptive temporal horizons.
Researched machine learning techniques for survival analysis, disease prediction, and cost analysis in healthcare. Applied new methods for training gradient boosted trees and recurrent neural networks to large healthcare datasets. Also developed high dimensional disease embeddings based on the field of natural language processing.
Explored graph symmetries and automorphisms. This is used to model the redundancies and patterns of large scale networks, allowing for both forecasting and separation of dynamical systems.