Enrico Bertini

schoolNew York Universitybar_chart#2353 Global Rank

Total Papers

HCI Rank

#2353

Research Areas

Years Active

Recent Publications

mTSeer: Interactive Visual Exploration of Models on Multivariate Time-series Forecast

Time-series forecasting contributes crucial information to industrial and institutional decision-making with multivariate time-series input. Although various models have been developed to facilitate the forecasting process, they make inconsistent forecasts. Thus, it is critical to select the model appropriately. The e…

CHI '215th+ AuthorInteractive Data Visualization +1

Mapping the Landscape of COVID-19 Crisis Visualizations

In response to COVID-19, a vast number of visualizations have been created to communicate information to the public. Information exposure in a public health crisis can impact people’s attitudes towards and responses to the crisis and risks, and ultimately the trajectory of a pandemic. As such, there is a need for work…

CSCW '20CorrespondingInterpreting and Explaining AI

Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs

As the use of machine learning (ML) models in product development and data-driven decision-making processes became pervasive in many domains, people's focus on building a well-performing model has increasingly shifted to understanding how their model works. While scholarly interest in model interpretability has grown…

CHI '202nd AuthorHonorable MentionInteractive Data Visualization +1

Truncating the Y-Axis: Threat or Menace?

Bar charts with y-axes that don't begin at zero can visually exaggerate effect sizes. However, advice for whether or not to truncate the y-axis can be equivocal for other visualization types. In this paper we present examples of visualizations where this y-axis truncation can be beneficial as well as harmful, dependin…

UIST '18CorrespondingInteractive Data Visualization +1

The Exploratory Labeling Assistant: Mixed-Initiative Label Curation with Large Document Collections

In this paper, we define the concept of exploratory labeling: the use of computational and interactive methods to help analysts categorize groups of documents into a set of unknown and evolving labels. While many computational methods exist to analyze data and build models once the data is organized around a set of pr…

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