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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ACROSS
In Progress
Actionable, Collaborative, Reusable, interOperable Sepsis System
Health & Biomedical
Dedgeflow
Completed
Using Data Science and Edge Computing for Debris Flow Warning
Climate & Environment
Academia
LUCID National Data Stream
In Progress
Low Value of Care in Medical Hospitalized Patients - a National Data Stream on Quality of Care in Swiss University Hospitals
Health & Biomedical
Public sector
Academia
AI-Driven Political Monitoring
Completed
Legislative tracking for labor advocacy at Kaufmännischer Verband Schweiz
Digital Society
Private sector
BioAIRad
In Progress
Biodiversity monitoring of the AIrspace with Radars
Climate & Environment
Academia
CleaRIS
Completed
Cleantech Recommendation and Intelligence System
Climate & Environment
Energy & Sustainability
Academia
Private sector
MAGNIFY
In Progress
Machine learning Assisted larGe scale quaNtIfication of building energy FlexibilitY
Energy & Sustainability
Large-scale Infrastructures
Academia
SPI-GreenFjord
In Progress
Climate & Environment
Academia
SPI-PAMIR
In Progress
Climate & Environment
Academia
Fore[st]cast
In Progress
Nowcast and predict forest condition
Climate & Environment
Academia
SDATE
In Progress
Smart Data Acquisition for Tomoscopy Experiments
Large-scale Infrastructures
Academia
LETITIA
In Progress
Learning tumor dynamics and early markers of immunotherapy response from PET/CT imaging
Health & Biomedical
Academia
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
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