Collaborative Projects
The goal of the SDSC Collaborative Projects is to help researchers and domain experts leverage the state-of-the-art in data science and at the same time, aim to support the application of techniques developed in research labs working on data science methods to real-world scenarios.
The scope of these Collaborative Data Science Projects is representative of the diversity of the research undertaken within the ETH Domain.

ArcticNAP – Exploring the Natural Aerosol baseline for improved model Predictions of Arctic climate change

SMARTAIR – Self-guided Machine Learning Algorithms for Real-Time Assimilation, Interpolation and Rendering of Flow Data

PolyNet – Exploring disease trajectories and outcome prediction in network analysis and machine learning

RenSho – Creating a comprehensive platform to enhance reproducibility in data-science driven research with Renku and Shogun
