Visual Analytics for Machine Learning

This project addresses the fundamental research problem of visualization for machine learning (Vis4ML). Our goal is to open the black box of machine learning (ML) to human users, making ML models more transparent, controllable, and modifiable through visual analytics. In particular, we will consider the following research directions to address this objective. First, we plan to employ surrogates as vehicles to reduce the complexity of the full ML models and make meaningful information accessible to humans. Second, we will develop constraint visualizations to integrate physical constraints in Vis4ML. Third, we will investigate language-based and guided user interaction to ease the exploration of ML models. Finally, one research direction is to harness the power of ML to further improve Vis4ML. In a collaborative effort with other SimTech members, we will explore several application scenarios for visual analytics for ML.