At Montana State University's NISL Research Group, I developed software for inference with Bayesian Networks and Continuous Time Bayesian Networks for automated testing systems. My work included backend algorithm and performance optimization, as well as frontend application development.
With QuBBD/CompTaG, I designed and implemented methods combining topological data analysis and computer vision to automate grading of prostate cancer histopathology images. I also built deep convolutional network models for prostate cancer detection.
My research spans statistical methodology, machine learning, and scientific software. I developed the C++ datamunge library, which binds its API to more than 10 languages, and have contributed to research on Bayesian modeling, uncertainty quantification, and topological data analysis.
