TACKLING COMPLEX PROBLEMS
My research focuses on the intersection of machine learning, explainable AI, and interactive sensemaking to help explain the outputs of artificial intelligence models. I am interested in developing applications that leverage machine learning to assist individuals in extracting and synthesizing information from large datasets while maintaining model interpretability and transparency.
I am currently working on an algorithm for automatically extracting coherent narratives from unstructured text data. This research has applications ranging from information synthesis in digital journalism to insight discovery in intelligence analysis. It builds up on previous research from Keith and Mitra and Shahaf et al. by providing an efficient method for single-pair (or "main-route") narrative extraction in large corpora and complex networks.
More details coming soon.