I am an Associate Professor at NYU Tandon School of Engineering in the CSE Department. In my lab we develop and study how to analyze and communicate data effectively with interactive visual interfaces.
I teach Information Visualization and Data Sensemaking to undergraduate and graduate engineering students at NYU Tandon. I also teach an online Specialization in Information Visualization for Coursera (open to anyone for free!).
The Exploratory Labeling Assistant: Mixed-Initiative Label Curation with Large Document Collections. Cristian Felix, Aritra Dasgupta, Enrico Bertini. Proc. of ACM User Interface Software and Technology Symposium (UIST), 2018.
RuleMatrix: Visualizing and Understanding Classifiers with Rules. Yao Ming, Huamin Qu, Enrico Bertini. IEEE Transactions on Visualization and Computer Graphics (Proc. of VAST), 2018. [Project Page]
Lessons Learned Developing a Visual Analytics Solution for Investigative Analysis of Scamming Activities. Jay Koven, Cristian Felix, Hossein Siadati, Markus Jakobsson and Enrico Bertini. IEEE Transactions on Visualization and Computer Graphics (Proc. of VAST), 2018.
A User Study on the Effect of Aggregating Explanations for Interpreting Machine Learning Models. Josua Krause, Adam Perer, Enrico Bertini. KDD Workshop on Interactive Data Exploration and Analytics (IDEA), 2018.
Taking Word Clouds Apart: An Empirical Investigation of the Design Space for Keyword Summaries. Cristian Felix, Steven Franconeri, Enrico Bertini. IEEE Transactions on Visualization and Computer Graphics (Proc. of InfoVis), 2017. [GitHub Page]
A Workflow for Visual Diagnostics of Binary Classifiers using Instance-Level Explanations. Josua Krause, Aritra Dasgupta, Jordan Swartz, Yindalon Aphinyanaphongs, Enrico Bertini. Proc. of IEEE Conference and Visual Analytics Science and Technology (VAST), 2017. [GitHub Page]
Interpreting Black-Box Classifiers Using Instance-Level Visual Explanations.
Paolo Tamagnini, Josua Krause, Aritra Dasgupta, Enrico Bertini. Proc. of SIGMOD Workshop on Human-In-the-Loop Data Analytics (HILDA), 2017 [Project Page].
Showing People Behind Data: Does Anthropomorphizing Visualizations Elicit More Empathy for Human Rights Data? Jeremy Boy, Margaret Satterthwaite, Anshul Vikram Pandey, Oded Nov, John Emerson, Enrico Bertini. Proc. of ACM CHI Conference on Human Factors in Computing Systems (CHI), 2017. [Blog Post].
[New!] Aug 6, 2018. You can now take our Information Visualization course online for free in Coursera!
[New!] Aug 1, 2018. We have two new papers at IEEE VAST (one on visualizing ML models and one on visualizing scamming data) and one at UIST (on interactive labeling for classification).
Jan 2018. I have been promoted to Associate Professor (with tenure)!
Apr 16, 2017. New paper at HILDA Workshop: "Interpreting Black-Box Classifiers Using Instance-Level Visual Explanations".
Feb 1, 2017. New ACM CHI paper: "Showing People Behind Data: Does Anthropomorphizing Visualizations Elicit More Empathy for Human Rights Data?"
Aug 2, 2016. New IEEE VAST paper: "TextTile: An Interactive Visualization Tool for Seamless Exploratory Analysis of Structured Data and Unstructured Text."
Jun 23, 2016. We presented: "Using Visual Analytics to Interpret Predictive Machine Learning Models." at the ICML Workshop on Human Interpretability in Machine Learning.
Jun 6, 2016. Student projects of our Information Visualization (Spring'16) course are online on GitHub.
May 27, 2016. Washington Post data analysis done by ProPublica with RevEx, our review analysis software: "Doctors fire back at bad Yelp reviews — and reveal patients’ information online".