Enabling data-driven science & innovation for societal impact

We accompany the academic community and the industrial sector in their data science journey, putting to work AI and ML and facilitating the multidisciplinary exchange of data and knowledge.

In the spotlight

EVENTS

Data Science for the Sciences

The first Swiss conference on Data Science for the Sciences.
April 11, 2024
BLOG

The Promise of AI in Pharmaceutical Manufacturing

PROJECT

CLIMIS4AVAL

Real-time cleansing of snow and weather data for operational avalanche forecasting
CASE STUDIES

Repositioning drugs for a rare disease

About

The Swiss Data Science Center

In 2017, a national Data Science initiative from the ETH Board resulted in the creation of a unique joint venture between EPFL and ETH Zurich: the Swiss Data Science Center.

The Center’s mission is to accelerate the use of data science and machine learning techniques within academic disciplines of the ETH Domain, the Swiss academic community at large, and the industrial sector.

Domains OF EXPERTISE

Meet our speakers and experts and gain knowledge with industry professionals.

collaborate

Innovation solutions for organizations

Through proofs of concept, talent transfers, academic expertise, objective feedback and more, we offer data science services to a wide variety of industries.

Next Events

Join us on our next events

Data Science for the Sciences

Apr 11, 2024
Apr 12, 2024
Casino Bern
Speaker(s):

News

Latest news

The Promise of AI in Pharmaceutical Manufacturing
April 22, 2024

The Promise of AI in Pharmaceutical Manufacturing

The Promise of AI in Pharmaceutical Manufacturing

Innovation in pharmaceutical manufacturing raises key questions: How will AI change our operations? What does this mean for the skills of our workforce? How will it reshape our collaborative efforts? And crucially, how can we fully leverage these changes?
Efficient and scalable graph generation through iterative local expansion
March 20, 2024

Efficient and scalable graph generation through iterative local expansion

Efficient and scalable graph generation through iterative local expansion

Have you ever considered the complexity of generating large-scale, intricate graphs akin to those that represent the vast relational structures of our world? Our research introduces a pioneering approach to graph generation that tackles the scalability and complexity of creating such expansive, real-world graphs.
RAvaFcast | Automating regional avalanche danger prediction in Switzerland
March 6, 2024

RAvaFcast | Automating regional avalanche danger prediction in Switzerland

RAvaFcast | Automating regional avalanche danger prediction in Switzerland

RAvaFcast is a data-driven model pipeline developed for automated regional avalanche danger forecasting in Switzerland. It combines a recently proposed classifier for avalanche danger prediction at weather stations with a spatial interpolation model and a novel aggregation strategy to estimate the danger levels in predefined wider warning regions, ultimately assembled as an avalanche bulletin.

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Contact us for your next Data Science project!