Olga Fink

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olga.fink@epfl.ch +41 21 693 66 29

EPFL ENAC IIC IMOS
GC A3 424 (Bâtiment GC)
Station 18
1015 Lausanne

+41 21 693 66 29
Office: GC A3 424
EPFL > ENAC > IIC > IMOS

Web site: Web site: https://IMOS.epfl.ch

+41 21 693 66 29
EPFL > ENAC > ENAC-SGC > SGC-ENS

+41 21 693 66 29
EPFL > VPA-AVP-DLE > AVP-DLE-EDOC > EDCE-GE

Web site: Web site: https://go.epfl.ch/phd-edce

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EPFL > VPA-AVP-DLE > AVP-DLE-EDOC > EDRS-GE

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EPFL > VPA-AVP-DLE > AVP-DLE-EDOC > EDCE-ENS

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Administrative data

Teaching & PhD

Teaching

Civil Engineering

PhD Students

Faghih Niresi Keivan, Garmaev Sergei, Sharma Vinay, Sun Han, Theiler Raffael Pascal, Von Krannichfeldt Leandro, Wei Amaury Pierre Jiezhi, Xu Chenghao, Zhang Zepeng, Zhao Mengjie,

Past EPFL PhD Students

Nejjar Ismail ,

Courses

Introduction to machine learning for engineers

Machine learning is a sub-field of Artificial Intelligence that allows computers to learn from data, identify patterns and make predictions. As a fundamental building block of the Computational Thinking education at EPFL, Civil students will learn ML with civil case studies (summary generated by ML)

Data Science for infrastructure condition monitoring

The course will cover the relevant steps of data-driven infrastructure condition monitoring, starting from data acquisition, going through the steps pre-processing of real data, feature engineering to developing suitable machine learning algorithms.

Machine learning for predictive maintenance applications

The course aims to develop machine learning algorithms capable of efficiently detecting faults in complex industrial and infrastructure assets, isolating their root causes, and ultimately predicting their remaining useful lifetime.

Frontiers of Deep Learning for Engineers

The seminar aims at discussing recent research papers in the field of deep learning, implementing the transferability/adaptability of the proposed approaches to applications in the field of research of the Ph.D. student.