This week we have a Post-Doc from AIMS-South Africa, *Pierre-Yves Lablanche,* giving a talk on *Nov 3* at* 10:30AM* in room *AA6214*
If anyone is interested in talking with Pierre-Yves about collaborating, hearing about different datasets/challenges, or is just interested in having a 1:1 chat, email me and I'll set it up!
Sorry for the late email! Michael
*KEYWORDS *Astronomy/Astrophysics, Statistical ML, Big Data
*TITLE *Machine Learning for Astronomy
*ABSTRACT* Astronomy and astrophysics like many other scientific field is entering the big data era. Observational instruments such as the Large Synoptic Survey Telescope (LSST) and the Square Kilometre Array (SKA) will produce hundreds of petabytes of data per year supporting many scientific projects and existing analysis and processing tools will not be sufficient to tackle the upcoming “big data” challenge. As a consequence a lot of focus has been given to machine learning techniques both supervised and unsupervised over the past years. In this talk I will present a case study of galaxies identification using unsupervised learning and discuss the results evaluation as well as the method application to future astronomical data. In addition I will give insights about some of the latest machine learning technique being used and developed within the astronomical community.
*BIO* Dr. Pierre-Yves Lablanche, born in Saint-Etienne in France, completed a BSc. in Physics and Chemistry at the Université Jean Monnet in Saint- Etienne in 2006 and a MSc. in Physics at the Univsersité Lyon 1 in 2008. He did his Ph.D. in astrophysics between Lyon and the European Southern Observatory (Münich, Germany) investigating the dynamics of barred galaxies via N-body simulations until 2012. The Ph.D. years were followed by two years of work as a scientific educator in a local association in Saint-Chamond (France) before volunteering to become a tutor at the African Institute for Mathematical Sciences (AIMS) in Arusha (Tanzania) in September 2014. A year later he joined the AIMS research centre in Cape Town (South Africa) where he is still working as a postdoctoral research fellow.
Although his Ph.D. focused on astrophysics, Pierre-Yves nowadays develop and applies machine learning techniques in various field such as astronomy, anthropology, text analysis and infrastructure development. Aside from his research he is involved in many science outreach activities in France, Tanzania and South Africa and collaborates with the International Astronomical Union Office of Astronomy for Development on various international projects. Dr. Lablanche more specifically focuses on activities toward minorities and disabled people humbly trying to make a little difference everywhere he goes, strongly believing that “Education is the most powerful weapon which you can use to change the world” (Nelson Mandela).
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This is in 30 minutes! Come on down!
On Tue, Oct 31, 2017, 15:18 Michael Noukhovitch mnoukhov@gmail.com wrote:
This week we have a Post-Doc from AIMS-South Africa, *Pierre-Yves Lablanche,* giving a talk on *Nov 3* at* 10:30AM* in room *AA6214*
If anyone is interested in talking with Pierre-Yves about collaborating, hearing about different datasets/challenges, or is just interested in having a 1:1 chat, email me and I'll set it up!
Sorry for the late email! Michael
*KEYWORDS *Astronomy/Astrophysics, Statistical ML, Big Data
*TITLE *Machine Learning for Astronomy
*ABSTRACT* Astronomy and astrophysics like many other scientific field is entering the big data era. Observational instruments such as the Large Synoptic Survey Telescope (LSST) and the Square Kilometre Array (SKA) will produce hundreds of petabytes of data per year supporting many scientific projects and existing analysis and processing tools will not be sufficient to tackle the upcoming “big data” challenge. As a consequence a lot of focus has been given to machine learning techniques both supervised and unsupervised over the past years. In this talk I will present a case study of galaxies identification using unsupervised learning and discuss the results evaluation as well as the method application to future astronomical data. In addition I will give insights about some of the latest machine learning technique being used and developed within the astronomical community.
*BIO* Dr. Pierre-Yves Lablanche, born in Saint-Etienne in France, completed a BSc. in Physics and Chemistry at the Université Jean Monnet in Saint- Etienne in 2006 and a MSc. in Physics at the Univsersité Lyon 1 in 2008. He did his Ph.D. in astrophysics between Lyon and the European Southern Observatory (Münich, Germany) investigating the dynamics of barred galaxies via N-body simulations until 2012. The Ph.D. years were followed by two years of work as a scientific educator in a local association in Saint-Chamond (France) before volunteering to become a tutor at the African Institute for Mathematical Sciences (AIMS) in Arusha (Tanzania) in September 2014. A year later he joined the AIMS research centre in Cape Town (South Africa) where he is still working as a postdoctoral research fellow.
Although his Ph.D. focused on astrophysics, Pierre-Yves nowadays develop and applies machine learning techniques in various field such as astronomy, anthropology, text analysis and infrastructure development. Aside from his research he is involved in many science outreach activities in France, Tanzania and South Africa and collaborates with the International Astronomical Union Office of Astronomy for Development on various international projects. Dr. Lablanche more specifically focuses on activities toward minorities and disabled people humbly trying to make a little difference everywhere he goes, strongly believing that “Education is the most powerful weapon which you can use to change the world” (Nelson Mandela).
lisa_seminaires@iro.umontreal.ca
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Michael Noukhovitch