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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Tigen: Augmented cell therapies
Completed
An artificial intelligence-based system for augmented cell & gene therapies
Health & Biomedical
Private sector
MLfusion
In Progress
Machine Learning for Disruption Prediction in Tokamaks
Large-scale Infrastructures
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
SFOE Energy Dashboard
Completed
Modelling the end-user Swiss electricity consumption
Energy & Sustainability
Public sector
Bühler: Enhancing resource efficiency
Completed
Data science for enhancing resource efficiency in manufacturing
Energy & Sustainability
Private sector
ICRC: Patterns of violence
Completed
Monitoring patterns of violence with data science
Digital Society
NGO
Adecco: Standardizing Job Titles
Completed
Job title standardization through entity alignment of knowledge graphs
Digital Society
Private sector
Sanfilippo: Drug Repositioning
Completed
Applying deep learning to repurpose drugs for the Sanfilippo syndrome treatment.
Health & Biomedical
NGO
DUPLET
In Progress
DUal Positron Lifetime Emission Tomography
Health & Biomedical
DS4MS
Completed
Data Science for Multiplexing Spectrometers
Large-scale Infrastructures
CHEMSPEC
Completed
Cost-effective chemical speciation monitoring of particulate matter air pollution
Climate & Environment
Chemistry
DATSSFLOW
Completed
Data Science and Mass Movement Seismology: Towards the Next Generation of Debris Flow Warning
Climate & Environment
WATRES
Completed
A Data-Driven approach to estimate WATershed RESponses
Climate & Environment
CLIMIS4AVAL
Completed
Real-time cleansing of snow and weather data for operational avalanche forecasting
Climate & Environment
ML4FCC
Completed
Machine Learning for the Future Circular Collider Design
Large-scale Infrastructures
PHENO-MINE
Completed
Pheno-Mine: Extracting dynamic ideotypes from seasonal image time series of wheat taken in the field
Climate & Environment
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