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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Dataspectrum4CVD
In Progress
Integrating medical image data and assessments for personalized cardiovascular risk estimation
Health & Biomedical
Academia
MedCare
In Progress
Detecting novel drug combinations associated with adverse events
Health & Biomedical
Academia
DataXAS
In Progress
Data science for X-ray Absorption Spectroscopy
Large-scale Infrastructures
Academia
COPE
In Progress
COnstraints on near-term warming ProjEctions via distributionally robust statistical and machine learning
Climate & Environment
Academia
MMAI-MS
Completed
Multi-Modal Analysis and Integration of MS Patient Data
Health & Biomedical
Academia
EUTHERMO
Completed
Scalable deep reinforcement learning algorithms for building climate control and energy management
Energy & Sustainability
Academia
ML-L3DNDT
Completed
Robust and scalable Machine Learning algorithms for Laue 3-Dimensional Neutron Diffraction Tomography
Large-scale Infrastructures
Academia
BioDetect
Completed
Deep Learning for Biodiversity Detection and Classification
Climate & Environment
Academia
STIMO
In Progress
Personalized epidural electrical stimulation of the lumbar spinal cord for clinically applicable therapy to restore mobility after paralyzing spinal cord injury
Health & Biomedical
Academia
LAMP
Completed
Lensless Actinic Metrology for EUV Photomasks
Large-scale Infrastructures
Academia
HighFEM
In Progress
High Frequency Earthquake Modelling
Climate & Environment
Academia
Inter-Detect
In Progress
Quantifying Plant-Pollinator Interactions Using Computer Vision
Climate & Environment
Academia
DS4MS
Completed
Data Science for Multiplexing Spectrometers
Large-scale Infrastructures
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
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Our team of data scientists and professionals looks forward to engaging in impactful, results-driven collaborations with you.