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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ML-L3DNDT
Completed
Robust and scalable Machine Learning algorithms for Laue 3-Dimensional Neutron Diffraction Tomography
Large-scale Infrastructures
EUTHERMO
Completed
Scalable deep reinforcement learning algorithms for building climate control and energy management
Energy & Sustainability
IRMA
Completed
Interpretable and Robust Machine Learning for Mobility Analysis
Engineering
ArcticNAP
Completed
Arctic climate change: Exploring the Natural Aerosol baseline for improved model Predictions
Climate & Environment
SEMIRAMIS
Completed
AI-augmented Architectural Design
Engineering
RED-ML
Completed
Reduction of high volume experimental data using machine learning
Large-scale Infrastructures
MLTox
Completed
Enhancing toxicological testing through machine learning
Climate & Environment
MACH-Flow
Completed
Machine learning for Swiss river flow estimation
Climate & Environment
DeepCloud
Completed
A data-driven sub-grid parametrization for complex terrain
Climate & Environment
4D-Brains
Completed
Extracting Activity from Large 4D Whole-Brain Image Datasets
Biology
DDForms
Completed
Data driven fast optimization of resonant metamaterial structures
Engineering
SMARTAIR
Completed
Self-guided Machine Learning Algorithms for Real-Time Assimilation, Interpolation and Rendering of Flow Data
Engineering
NLP
Completed
Narratives in Law and Politics: A Computational Linguistics Approach
Digital Society
PolyNet
Completed
Exploring disease trajectories and outcome prediction using novel methods in network analysis and machine learning
Health & Biomedical
4Real
Real-time urban pluvial flood forecasting
Climate & Environment
MLATEM
Machine Learning tools for Analytical Transmission Electron Microscopy
Chemistry
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