The Swiss Data Science Center

Enabling data-driven science and innovation for societal impact, and supporting scientists, businesses and organizations in data science.
In 2017, a national Data Science initiative from the ETH Board resulted in the creation of a unique joint venture: the Swiss Data Science Center, bringing together the ETH Zürich, the EPFL, and the PSI . 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, the public institutions and the industrial sector.

A team of senior data scientists and experts in domains such as personalized health & medicine, earth & environmental science, social sciences, digital humanities and economics collaborate on academic and industrial projects. This unique positioning, at the crossroad of academic excellence and a fast-paced business environment, is key to simplifying a complex data science journey.

Team

A diversified team of researchers and professionals in Data Science

Phillip Agredazywczuk
Phillip Agredazywczuk
PostDoc
Liliana Barrios
Liliana Barrios
Sr. Data Scientist
Chiara Preti
Chiara Preti
Data Scientist
François Kamper
François Kamper
Sr. Data Scientist
Tasko Olevski
Tasko Olevski
Sr. Software Engineer
Daniel Trejo Banos
Daniel Trejo Banos
Sr. Data Scientist

Open Research

Promoting Open Research

promote open research in data science
At the SDSC, we promote open research practices throughout the entire data lifecycle.

By leveraging our expertise in semantic enablement, data governance, privacy and security, and other key areas, we help our partners and ecosystem actors to adopt open research practices that maximize the impact and reuse of their research outputs.

News

Latest news

Smartair | An active learning algorithm for real-time acquisition and regression of flow field data
May 1, 2024

Smartair | An active learning algorithm for real-time acquisition and regression of flow field data

Smartair | An active learning algorithm for real-time acquisition and regression of flow field data

We’ve developed a smart solution for wind tunnel testing that learns as it works, providing accurate results faster. It provides an accurate mean flow field and turbulence field reconstruction while shortening the sampling time.
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.

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