Data Science Projects
Our Collaborative Data Science Projects represent the diversity of the research and innovation undertaken in data science and AI within the ETH Domain, with scientific partners and with private and public sector stakeholders.
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LEAP
Completed
LEArning to Print – towards data-driven real-time predictions for additive manufacturing
Engineering
Academia
DNAi
Completed
High throughput eDNA processing using artificial intelligence for ecosystem monitoring
Climate & Environment
Academia
PHENO-MINE
Completed
Pheno-Mine: Extracting dynamic ideotypes from seasonal image time series of wheat taken in the field
Climate & Environment
Academia
DATSSFLOW
Completed
Data Science and Mass Movement Seismology: Towards the Next Generation of Debris Flow Warning
Climate & Environment
Academia
FastPoints2Mesh
In Progress
Data-Driven Inference of Mesh-based Representations for Deformable Objects from Unstructured Point Clouds
Engineering
Academia
PAIRED-HYDRO
Completed
Machine learning for the components fatigue prediction in hydropower generation
Energy & Sustainability
Engineering
Academia
ML-ED
Completed
Increased spatial resolution in electron detectors through machine learning
Large-scale Infrastructures
Academia
DIMPEO
Completed
Detecting drought impacts on forests in earth observation data
Climate & Environment
Academia
FastPlasmaSim
In Progress
Acceleration of Free-boundary Grad-Shafranov codes using advanced numerical methods
Large-scale Infrastructures
Academia
CHIP
In Progress
MaCHIne-Learning-assisted Ptychographic nanotomography
Large-scale Infrastructures
Academia
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