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1st Edition of the School in 

Machine Learning of 

Dynamic Processes and Time Series Analysis

26-27 NOVEMBER , 2020

Scuola Normale Superiore

Pisa

In Brief
The aim of the School is to present recent developments in Machine Learning focusing on data-driven approaches to statistical learning and dynamical systems. Applications will also be discussed, such as the forecasting of financial time series.
The School provides 4 lectures by: 
In addition, it provides a limited number of contributed talks
(Agenda and abstracts of the contributed talks are now online!).

IMPORTANT INFORMATION CONCERNING THE Covid-19

Due to the current worldwide situation due to the Covid-19 pandemic, the School can be attended only in on-line mode.
We gratefully acknowledge the contribution of various sponsors for financial support. In particular, the School is supported by:
  • The scheme 'INFRAIA-01-2018-2019: Research and Innovation action', Grant Agreement n. 871042 'SoBigData++: European Integrated Infrastructure for Social Mining and Big Data Analytics'. www.sobigdata.eu.
  • The "Department of Excellence" of the Scuola Normale Superiore.
  • Unicredit Group, under the project ‘‘Dynamics and Information Research Institute-QuantumInformation, Quantum Technology.
Flyer
Flyer of the conference: DOWNLOAD
 
Deadlines​
  • ​Paper submission and Registration closes on September 30th, 2020.
In order to register for the School or if you want to give a contributed talk, please follows the directions that you find when pressing the button "Apply" here below.
Organizer Committee
Fabrizio Lillo (University of Bologna and Scuola Normale Superiore);
Giulia Livieri (Scuola Normale Superiore); 
Stefano Marmi (Scuola Normale Superiore);
Piero Mazzarisi (Scuola Normale Superiore).
To contact the Organizer Committee, please write an email to : mldyn2020@sns.it

The Speakers

01

Christa Cuchiero

University of Vienna

Christa Cuchiero is Full Professor for Quantitative Risk Management at the Institute for Statistics and Operations Research at the University of Vienna since March 2020. Her interests include Machine Learning in Finance; Insurance and Economics; Mathematical Finance; Statistics of Stochastic Processes and with High-Frequency data.

Lyudmila Grigoryeva

University of Konstanz

Lyudmilla Grigoryeva is an Assistant Professor in Computational Statistics and Econometrics at the Department of Mathematics and Statistics Graduate School of Decision Science at the University of Konstanz since October 2015. Her interests include Machine Learning in Econometrics; Stochastic Dynamical Models in Mathematical Finance and Econometrics; Brain-inspired Information processing.

02

03

Juan-Pablo Ortega

University of St. Gallen

Juan-Pablo Ortega is a Professor PhD and Big Data Project Leader at the Faculty of Mathematics and Statistics at the University of St. Gallen since 2016 and a Senior CNRS researcher (on leave). His interests include Machine Learning and Statistical Modeling to time series; Financial Econometrics; Mathematical Finance. 

Josef Teichmann

ETH Zurich

Josef Teichmann is Full Professor in Mathematics at ETH Zurich since 2009. His interests include Machine Learning, especially the mathematical foundation of Machine Learning; Stochastic Analysis; Mathematical Finance; Portfolio Management, as well as Frontier Topics such as Big Data and Fintech.

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04

 
 

Final

Agenda

NOVEMBER, 26, 2020

8:45

Opening Remarks

9:00

11:30

Online Coffee Break 

12:00

13:20

Lunch break

15:00

NOVEMBER, 27, 2020

9:00

11:30

Online Coffee Break 

12:00

13:00

Lunch break

14:30

17:00

Concluding Remarks

 
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Venue & Accommodation

The school will take place in the main building of the Scuola Normale Superiore, located in Piazza dei Cavalieri 7, 56126, Pisa, Italy. The lecture hall are the "Sala Azzurra" (1st floor) and the "Sala Degli Stemmi" (2nd floor) and "Aula Dini" (Palazzo del Castelletto).

GETTING TO PISA

  • The Airport of Pisa (Galileo Galilei International Airport) is near the city center, and it is served by major airlines with flights from Milan, Rome, London, Paris and many other Italian, European and international cities.  

  • The Florence Airport (Firenze-Peretola Airport) is the next closest airport to the city of Pisa; it also has numerous connection to Italian, European and international cities. It is linked to the central train station (Santa Maria Novella) of Florence by shuttle buses and by train to Pisa. These trains leave approximately every twenty minutes. It takes about an hour to travel from Florence to Pisa.

  • Other possible airports that may be convenient are those of Rome (ADR).

GETTING TO THE SCUOLA NORMALE SUPERIORE

  • By bus.  Scuola Normale can be reached from the Pisa Airport using city buses (Compagnia Toscana Trasporti): take the LAM rossa (red) bus, which directly connects the airport with the city centre.
    The “via Fermi” stop is the nearest to Scuola Normale.

  • By taxi. You can also take a taxi (CoTaPi);  the trip from the airport to the Scuola Normale costs about €10. Tel.: (+39)050541600.

  • By train. The main station is “Pisa Centrale”, located in the city centre about 1 km from the Scuola Normale. Pisa is connected with all main European cities by train through Florence, Turin, Genoa or Rome (Trenitalia).

HOTELS: Hotels.

 

RESTAURANTS: Restaurants.

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