About

About Data Intensive Studies Center (DISC)

DISC image describing the team and what DISC is about.

Data sciences enable transformative research in many disciplines. However, initiating and sustaining such work can be difficult and needs partners and expertise that may be difficult to find. The scope, challenges and outcomes requires active and engaged partnerships among disciplinary and data scientists that are often hard to form and sustain. 

Data science related expertise is a core skill in most organizations and both Tufts’ current students and many in the communities Tufts serves need access to high quality education and training in these domains.

The Data Intensive Studies Center (DISC) will enable Tufts scholars and students to address these needs.

DISC will be sustaining institutionalizing TRIPODs initiatives. Learn more about TRIPODs activities at Tufts. 

Our Mission

To enable excellence in data science scholarship and education at Tufts University.

Data science enables transformative research in many disciplines, but initiating and sustaining such efforts requires a focused entity to drive those goals forward. DISC is an evolving entity that fills the gap: we add value by creating long-lasting and engaged partnerships among disciplinary experts and data scientists, while exposing students and the Tufts community to high quality education and scholarship in data science topics. 

DISC accomplishes its mission by

Organizing events to engage with the Tufts community and disseminate passion for data science

Offering workshops and courses on data science topics within Tufts University for undergraduate and graduate students

Providing students with real research experience through internships

Engaging with disciplinary experts from within Tufts University and outside institutions to identify research gaps that data science can transform

Enabling faculty that want to bring data science in their research through fellowships and seed grants

Receiving research funding from a wide range of sources in the government and academia to drive “Data Science + X” innovation