Lenka Zdeborová
EPFL SB IPHYS SPOC1
BSP 722 (Cubotron UNIL)
Rte de la Sorge
1015 Lausanne
+41 21 693 83 27
Office: BSP 722
EPFL › SB › IPHYS › SPOC1
Website: https://www.epfl.ch/labs/spoc/
+41 21 693 83 27
Office: BSP 722
EPFL › VPA › VPA-AVP-DLE › AVP-DLE-EDOC › EDPY-ENS
+41 21 693 83 27
Office: BSP 722
EPFL › IC › IC-SIN › SIN-ENS
Website: https://sin.epfl.ch
+41 21 693 83 27
Office: BSP 722
EPFL › SB › SB-SPH › SPH-ENS
Website: https://sph.epfl.ch/
+41 21 693 83 27
Office: BSP 722
EPFL › IC › IC-SSC › SSC-ENS
Website: https://ssc.epfl.ch
Teaching & PhD
Current Phd
Cédric Xavier Koller, Gabriele Farnè, Yizhou Xu, Yatin Dandi, Odilon Duranthon, Freya Behrens, Emanuele Troiani, Fabrizio Boncoraglio
Past Phd As Director
Hugo Chao Cui, Giovanni Piccioli, Lucas Andry Clarte
Courses
Data analysis for Physics
This lecture will introduce the basics of data analysis and learning from data, error estimation and stochasticity in physics. Concepts will be introduced theoretically as well as via numerical exercises done in Python.
Lecture series on scientific machine learning
This lecture presents ongoing work on how scientific questions can be tackled using machine learning. Machine learning enables extracting knowledge from data computationally and in an automatized way. We will learn on examples how this is influencing the very scientific method.
Machine learning for physicists
Machine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practised.