Clément Hongler

Edit profile

clement.hongler@epfl.ch +41 21 693 52 87 http://csft.epfl.ch

Citizenship: CH

Birth date: 30.11.1985

Phone

+41 79 884 69 57

EPFL SB MATH CSFT
MA C1 643 (Bâtiment MA)
Station 8
1015 Lausanne

+41 21 693 52 87
+41 21 693 52 93
Office: MA C1 643
EPFL > SB > MATH > CSFT

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

+41 21 693 52 87
EPFL > SB > SB-SMA > SMA-ENS

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

+41 21 693 52 87
EPFL > VPA-AVP-DLE > AVP-DLE-EDOC > EDMA-GE

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

vCard
Administrative data

Mission

Most of our research is devoted to statistical mechanics, quantum field theory and deep learning theory.

Key projects include:
--The investigation of the connection between lattice models and conformal field theories.
--The dynamics of learning, in particular that of neural networks during training.
--Artificial life, in particular continuous cellular automata.
--Decentralized systems.

Biography

2006: B.Sc. Math, EPFL
2008: M.Sc. Math, EPFL
2010: Ph.D. Math, Université de Genève
2010-2014: Ritt Assistant Professor, Columbia University
2014-2018: Tenure-Track Assistant Professor, EPFL
2019-present: Associate Professor, EPFL

Teaching & PhD

Teaching

Mathematics

PhD Students

Bendjeddou Amire, Dakhmouche Ramzi Sofiane,

Past EPFL PhD Students

Golikov Evgenii , Jacot-Guillarmod Arthur Ulysse , Park Sung Chul , Simsek Berfin , Spadaro Francesco ,

Courses

Analysis III - complex analysis and vector fields

To learn the basic tools of vector analysis and complex analysis.

Lattice models

Lattice models consist of (typically random) objects living on a periodic graph. We will study some models that are mathematically interesting and representative of physical phenomena seen in the real world.

Artificial Life

We will give an overview of the field of Artificial Life (Alife). We study questions such as emergence of complexity, self-reproduction, evolution, both through concrete models and through mathematical results. We will describe some of the most influential Alife models, and learn to implement them.