Rate My Professor Enrico Bertini

Bertini's research centers on data visualization and visual analytics, developing interfaces to help users interpret complex data and machine learning models. His work explores visual interfaces for model exploration, validation, and understanding, alongside advancing theoretical and empirical insights into human extraction of information from visuals. Key interests include visual affordances in data visualization, visualization for situated data monitoring, and visualization literacy. He co-hosts the Data Stories podcast, discussing data's role in daily life. Notable publications include "Cognitive Affordances in Visualization: Related Constructs, Design Factors, and Framework" (Racquel Fygenson, Lace Padilla, Enrico Bertini, IEEE Transactions on Visualization and Computer Graphics, 2025); "Stitching Meaning: Practices of Data Textile Creators" (Sydney Purdue et al., IEEE TVCG, 2025); "PDPilot: Exploring Partial Dependence Plots Through Ranking, Filtering, and Clustering" (Daniel Kerrigan, Brian Barr, Enrico Bertini, IEEE TVCG, 2025); "Visual Exploration of Machine Learning Model Behavior with Hierarchical Surrogate Rule Sets" (Jun Yuan et al., IEEE TVCG, 2022); "Multiple Forecast Visualizations (MFVs): Trade-offs in Trust and Performance in Multiple COVID-19 Forecast Visualizations" (Lace Padilla et al., IEEE TVCG, 2023); and "Impact of COVID-19 Forecast Visualizations on Pandemic Risk Perceptions" (Lace Padilla et al., Scientific Reports, 2022). Bertini teaches data visualization courses to undergraduate and graduate students in engineering and design.