Invitation to the Joint ICTP-SISSA Webinar Colloquium by Prof. Andrea Montanari, Stanford University, on "What is Machine Learning and What We Don't Understand About It", on Wednesday 22 July at 16:00 hrs

[ICTP/director]

Dear All,

You are most cordially invited to the Joint ICTP-SISSA Webinar 
Colloquium byProf. Andrea Montanari, Stanford University, USA on "What 
is Machine Learning and What We Don't Understand About It", on Wednesday 
22 July at 16:00 hrs.

Pre-registration is required at the following url: 
https://zoom.us/webinar/register/WN_YK6VZDvDT3WdBljtsqhHWQ

After registering, you will receive a confirmation email containing 
information about joining the webinar.

The talk will be available on livestream via the ICTP website, and also 
on ICTP's YouTube channel.

Live screening in the Budinich Lecture Hall will be set up as well. Due 
to the safety measures that are in place, a maximum of 10 can attend by 
keeping distances and wearing a mask).

*Biosketch: *Andrea Montanari received a Laurea degree in Physics in 
1997, and a Ph. D. in Theoretical Physics in 2001 (both from Scuola 
Normale Superiore in Pisa, Italy). He has been post-doctoral fellow at 
Laboratoire de Physique Théorique de l'Ecole Normale Supérieure 
(LPTENS), Paris, France, and the Mathematical Sciences Research 
Institute, Berkeley, USA. Since 2002 he is Chargé de Recherche (with 
Centre National de la Recherche Scientifique, CNRS) at LPTENS. In 
September 2006 he joined Stanford University as a faculty, and since 
2015 he is Full Professor in the Departments of Electrical Engineering 
and Statistics. He was co-awarded the ACM SIGMETRICS best paper award in 
2008.

He received the CNRS bronze medal for theoretical physics in 2006, the 
National Science Foundation CAREER award in 2008, the Okawa Foundation 
Research Grant in 2013, and the Applied Probability Society Best 
Publication Award in 2015. He is an Information Theory Society 
distinguished lecturer for 2015-2016. In 2016 he received the James L. 
Massey Research & Teaching Award of the Information Theory Society for 
young scholars, and in 2017 was elevated to IEEE Fellow. In 2018 he was 
an invited sectional speaker at the International Congress of 
Mathematicians. He is an invited IMS Medallion lecturer for the 2020 
Bernoulli-IMS World Congress.

*Abstract: *The last fifteen years have witnessed dramatic breakthroughs 
in machine learning. This progress was crucially driven by engineering 
advances: greater computing power and larger availability of training 
data. Not only the collection of methods that emerged from this 
revolution are not well understood mathematically, but they actually 
appear to defy traditional mathematical theories of machine learning. 
Future developments and applications, especially within the sciences, 
will require to understand better the underlying mathematical 
principles. I will try to provide a gentle introduction to the subject, 
and a peek into some recent advances towards addressing these challenges.

The talk will be followed by a question/answer session.

For info, please check the following link: http://indico.ictp.it/event/9419/

We look forward to seeing you online!

With best regards,

Office of the Director, ICTP