Collaborative Project Information Day 2022
Presentation of the 6th Call
Presented by:
Dr. Guillaume Obozinski
Prof. Fernando Perez-Cruz (Deputy Chief & Chief Data Scientists at SDSC)
Dr. Michele Volpi
Dr. Ekaterina Krymova
Dr. Benjamín Béjar
Agenda
Starting Projects (5th call)
The goal of the SDSC Collaborative Projects is to help researchers and domain experts leverage the state-of-the-art in data science and at the same time, aim to support the application of techniques developed in research labs working on data science methods to real-world scenarios. The scope of these Collaborative Data Science Projects is representative of the diversity of the research undertaken within the ETH Domain.
In 2022, 14 projects were accepted in the main track, three projects in the Large Scale Infrastructure (LSI) track, and another three projects were co-funded with the Strategic Focus Area on Personalized Health and Related Technologies (PHRT). To learn more about PHRT, click HERE.
EXPECTmine
Mining Toxicity and High-Resolution Mass Spectrometry Data for Linking Exposures to Effects
Presented by:
Prof. Dr. Juliane Hollender
ML-SPOCK
Machine Learning Supported system for Performance assessment of steel structures under extreme Operating Conditions and management of risK.
Presented by:
Prof. Dr. Dimitrios Lignos
Pheno-Mine
Extracting dynamic ideotypes from seasonal image time series of wheat taken in the field
Presented by:
Prof. Dr. Achim Walter
DAAAD_Bridges
Domain-aware-AI Augmented Design of Bridge Structures
Presented by:
Dr. Ing. Michael Kraus
WATRES
A Data-Driven approach to estimate WATershed RESponses
Presented by:
Dr. Paolo Benettin
CHEMSPEC
Cost-effective chemical speciation monitoring of particulate matter air pollution
Presented by:
Dr. Satoshi Takahama
PAIRED-HYDRO
Machine learning for the components fatigue prediction in hydropower generation
Presented by:
Dr. Elena Vagnoni
DATSSFLOW
Data Science and Mass Movement Seismology: Towards the Next Generation of Debris Flow Warning
Presented by:
Dr. Fabian Walter
Mlfusion
Machine Learning for Disruption Prediction in Tokamaks
Presented by:
Dr. Olivier JL Sauter
DS4MS | LSI track
Data Science for Multiplexing Spectrometers
Presented by:
Dr. Daniel Gabriel Mazzone
LAMP | LSI track
Lensless Actinic Metrology for EUV Photomasks
Presented by:
Dr. Iacopo Mochi
sc_Drug | co-funded with PHRT
Predictive models of cell type drug sensitivity in Acute Myeloid Leukemia
Presented by:
Prof. Dr. Didier Trono
CLIMIS4AVAL | LSI track
Real-time cleansing of snow and weather data for operational avalanche forecasting
Presented by:
Prof. Dr. Jürg Schweizer