Hackathons are time-bounded events where participants gather in teams to develop projects
that interest them. Such events have been adopted in various domains to generate …

The number of hackathon events worldwide has nearly quadrupled in the last five years.
Despite exponential growth across diverse industries and increasing interest across …

The rapid advancement of artificial intelligence (AI) is changing our lives in many ways. One
application domain is data science. New techniques in automating the creation of AI, known …

Today, the prominence of data science within organizations has given rise to teams of data
science workers collaborating on extracting insights from data, as opposed to individual data …

The development of AI applications is a multidisciplinary effort, involving multiple roles
collaborating with the AI developers, an umbrella term we use to include data scientists and …

We explore trust in a relatively new area of data science: Automated Machine Learning
(AutoML). In AutoML, AI methods are used to generate and optimize machine learning …

Data is central to the development and evaluation of machine learning (ML) models.
However, the use of problematic or inappropriate datasets can result in harms when the …

In recent years there has been an increasing trend in which data scientists and domain
experts work together to tackle complex scientific questions. However, such collaborations …

Data science (DS) projects often follow a lifecycle that consists of laborious tasks for data
scientists and domain experts (eg, data exploration, model training, etc.). Only till recently …

Creating presentation slides is a critical but time-consuming task for data scientists. While
researchers have proposed many AI techniques to lift data scientists' burden on data …