Chaire Georges Lemaître 2017 in CP3

27 Nov 2017, 16:15 → 1 Dec 2017, 13:00 Europe/Brussels

E/3rd floor-E.349 - Seminar room (E.349) (Marc de Hemptinne (chemin du Cyclotron, 2, Louvain-la-Neuve))

Fabio Maltoni (UCL)

Physics, Statistics, and machine learning by Kyle Cranmer

Prof. Kyle Cranmer is the recipient of the 2017 Georges Lemaitre Chaire in CP3 .

He will give a inaugural lecture on Monday 27th of Nov. at 16:15 (CYCL01) and then a series of four 2h lectures (starting at 10:45, Tue-Fri, E.361)

CV (EN)

Kyle Cranmer is Associate Professor of Physics at New York University and affiliated with NYU’s Center for Data Science and CILVR Machine Lab. He is an experimental particle physicist working, primarily, on the Large Hadron Collider. Professor Cranmer obtained his Ph.D. in Physics from the University of Wisconsin-Madison in 2005 and his B.A. in Mathematics and Physics from Rice University. He was awarded the Presidential Early Career Award for Science and Engineering in 2007 and the National Science Foundation’s Career Award in 2009. Professor Cranmer developed a framework that enables collaborative statistical modeling, which was used extensively for the discovery of the Higgs boson in July 2012. His current interests are at the intersection of physics, statistics, and machine learning.

CV (FR)

Kyle Cranmer est Professeur de physique à la New York University et membre affilié aux Center for Data Science et CILVR Machine Lab de la New York University. Il est expérimentateur en physique des particules, essentiellement auprès du grand collisionneur de hadrons. Le professeur Cranmer a obtenu son doctorat en physique à l’Université de Wisconsin-Madison en 2005 et son B.A. en Mathématique et Physique à l’Université Rice. Il a reçu le « Presidential Early Career Award» en sciences et ingénierie en 2007 et le « National Science Foundation’s Career Award» en 2009. Le professeur Cranmer a développé un environnement qui permet une modélisation statistique collaborative, utilisé largement dans la découverte du boson de Higgs en juillet 2012. Ses centres d’intérêts actuels sont à la frontière entre la physique, la statistique et le machine learning.

Poster poster.pdf

Slides Lemaitre-Lectures.pdf

Monday, 27 November

1 Rethinking physics in the age of deep learning

Speaker: Prof. Kyle Cranmer (NYU)

Slides LemaitreInaguralLecture.pdf

17:30 Cocktail

Tuesday, 28 November

2 Physics, Statistics, and Machine Learning I

Speaker: Prof. Kyle Cranmer (NYU)

Slides Lemaitre-Lectures.pdf

Wednesday, 29 November

3 Physics, Statistics, and Machine Learning II

Thursday, 30 November

4 Physics, Statistics, and Machine Learning III

Friday, 1 December

5 Physics, Statistics, and Machine Learning IV