Enrico Bertini

Welcome!

I am an Associate Professor at Northeastern University, with a double appointment between Computer Science (Khoury) and Art/Media/Design (CAMD). I am a member of the Khoury Data Visualization Lab.

I teach courses on Data Visualization and related topics to undergraduate and graduate engineering and design students.

I have a newsletter where I write about my ideas on the world of data and data visualization. Sign up to receive my posts directly in your inbox.

Current main research interests

We are working mainly on the following questions/problems:

1. Visual interfaces for interpretable machine learning: How can we help people understand, verify, and interact with ML more effectively?

2. Affordance in data visualization: How can we apply the concept of affordance to data visualization? How do we describe the fact that visual cues in visualization suggest the type of information and message they communicate?

3. Visualization for situated data monitoring: How do we design data visualizations for data sets that change continuously over time?

4. Visualization literacy and data thinking: How do we teach people to think with data and data visualization? How do we measure and improve their data skills?

Latest Publications

The Arrangement of Marks Impacts Afforded Messages: Ordering, Partitioning, Spacing, and Coloring in Bar Charts. Racquel Fygenson, Steven Franconeri, Enrico Bertini. IEEE Transactions on Visualization and Computer Graphics (Proc. of IEEE VIS), 2023.

Visual Exploration of Machine Learning Model Behavior with Hierarchical Surrogate Rule Sets. Jun Yuan, Brian Barr, Kyle Overton, Enrico Bertini. IEEE Transactions on Visualization and Computer Graphics, 2022.

Multiple Forecast Visualizations (MFVs): Trade-offs in Trust and Performance in Multiple COVID-19 Forecast Visualizations. Lace Padilla, Racquel Fygenson, Spencer C Castro, Enrico Bertini. IEEE Transactions on Visualization and Computer Graphics (Proc. of IEEE VIS), 2022.

Impact of COVID-19 Forecast Visualizations on Pandemic Risk Perceptions. Lace Padilla, Helia Hosseinpour, Racquel Fygenson, Jennifer Howell, Rumi Chunara, Enrico Bertini. Scientific Reports volume 12, Article number: 2014 (2022).

Updates

Oct 2023. We have three papers presented at IEEE VIS. Two from Jun and one from Racquel (Whoo hoo! Her first first-author paper at VIS!).

Feb 2023. Congratulations to my student Jun Yuan who successfully defended her thesis on visualizing rule sets to understand machine learning models! Jun is now working at Apple.

Jan 2022. I moved to Boston! I am now at Northeastern University.

Sep 2021. We have two new short papers being presented at IEEE VIS. One on a visualization technique to analyze ML models with counterfactual explanations and one on a user study to understand the design space of classification rule visualizations.

May 2021. We have two new papers at ACM CHI. One on the analysis of COVID19 visualizations and one on visual exploration of forecasting models.

October 2020. We have a new IEEE VIS short paper out on the limitations of precision-driven visualization design.

June 2020. We have a new CSCW paper out on how practitioners deal with ML interpretability in industry.

May 2020. We have a new paper out on Truncating the Y-Axis in charts at CHI.

Mar 2020. We have two new papers out! One at IUI’20 on visualization for ML explanation and one at CHI’20 on studying charts with truncated axes.