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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I-DEEP-TRUST
In Progress
Develop interpretable and trustworthy deep learning models for treatment decisions in acute ischemic stroke patients
Health & Biomedical
Academia
SMARTT
In Progress
Smart sampling for small-angle x-ray scattering Tensor Tomography
Large-scale Infrastructures
Academia
MUTIGER
Completed
MUTations, Interactions and GEne Regulation
Health & Biomedical
Academia
TGSF-DA
In Progress
Data Analysis of the Turbulence and Gravity roles in Stellar Formation
Physics
Academia
MOBIKO
In Progress
Mountain Biodiversity Knowledge Graph
Climate & Environment
Academia
SCOPE
In Progress
Sources and drivers of organic aerosol pollution in Europe and response to global warming and net-zero policies
Climate & Environment
Academia
ECOCLIM
In Progress
Integrating ecological information into climate downscaling
Climate & Environment
Academia
Èvokâ: Enhancing Fribourg's Archives
Completed
Making 10 TB of cultural heritage searchable and emotionally resonant
Digital Society
Public sector
Academia
ACROSS
In Progress
Actionable, Collaborative, Reusable, interOperable Sepsis System
Health & Biomedical
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ADOPT
Completed
AI for Detecting Ocean Plastic Pollution with Tracking
Climate & Environment
Academia
Open-source RAG for Zurich SMEs
Completed
Canton Zurich AI Program generates a Retrieval-Augmented Generation prototype for SMEs
Digital Society
Engineering
Private sector
Timeseries Forecasting for Business Impact
Completed
Supporting Zurich SMEs in operational efficiency and decision-making
Digital Society
Private sector
ICRC: Patterns of violence
Completed
Monitoring patterns of violence with data science
Digital Society
NGO/IO
Merck: cancer care adverse events
Completed
Exploring how machine learning can help address cancer treatment side effects
Health & Biomedical
Private sector
Canton de Vaud: ENERBAT
Completed
Data-Driven Pathways to Net Zero for the Canton of Vaud’s Building Portfolio
Energy & Sustainability
Climate & Environment
Public sector
Xelidoni: TREMA
Completed
Transforming real estate management with AI
Engineering
Private sector
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Our team of data scientists and professionals looks forward to engaging in impactful, results-driven collaborations with you.