EAIA 2018 Commemorative Photo. Thank you everyone!

EAIA 2018 - DS4BD

Advanced School on Data Science for Big Data

Scope: Data Science and Big Data are not only hot topics but also essencial to current society. Economy, health, agriculture, energy, media, education, industry, mobility, leasure and all other human activities rely more and more on the advanced processing of large quantities of data.

This proposal is based on our large experience as lecturers and as organizers of previous Summer Schools such as "Summer School On Data Sciences For Big Data - Resource Aware Data Mining" in Porto, associated to ECML PKDD 2015 (www.ecmlpkdd2015.org/summer-school).

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Lecturers

Albert Bifet

  ParisTech
 Homepage
  Bio    Abstract

Alípio Jorge

  UP, INESC TEC
 Homepage
  Bio    Abstract

André Carvalho

  ICMC, Usp
 Homepage
  Bio    Abstract

Carlos Soares

 Homepage
  Bio    Abstract

Dino Pedreschi

  Univ of Pisa
  Bio    Abstract

EDP Speaker

  EDP
 Homepage
  Bio    Abstract

Fosca Giannotti

  ISTI-CNR
 Homepage
  Bio    Abstract

Gianmarco De Francisci Morales

  QCRI
  Bio    Abstract

Jorge M Soares

  IBM
 Homepage
  Bio    Abstract

Jose Carlos Principe

  University of Florida Gainesville
  Bio    Abstract

João Gama

 Homepage
  Bio    Abstract

João Gomes

  Farfetch
 Homepage
  Bio    Abstract

João Vinagre

 Homepage
  Bio    Abstract

Olivier Pietquin

  Google Brain
 Homepage
  Bio    Abstract

Pavel Brazdil

  LIAAD Inesc Tec
 Homepage
  Bio    Abstract

Pedro Larrañaga

  UPM, Madrid
 Homepage
  Bio    Abstract

Pedro P. Rodrigues

 Homepage
  Bio    Abstract

Pedro Ribeiro

  DCC/FCUP & CRACS
 Homepage
  Bio    Abstract

Rayid Ghani

  Univ. Chicago
 Homepage
  Bio    Abstract

Ricard Gavaldà

  UPC
 Homepage
  Bio    Abstract

Ricardo Baeza-Yates

  NTENT
 Homepage
  Bio    Abstract

Ricardo Galante

  SAS Institut
 Homepage
  Bio    Abstract

Rita P. Ribeiro

  UP, INESC TEC
 Homepage
  Bio    Abstract

Roy Cecil

  IBM
 Homepage
  Bio    Abstract

Schedule

Hour
9:00 - 10:45 Data Science for Big Data
André Carvalho  ICMC, Usp
 Lecture Slides
10:45 - 11:00 Coffee Break
11:00 - 13:00 DS for Social Good - Data Science for Social Good and Public Policy: Examples, Opportunities, and Challenges
Rayid Ghani  Univ. Chicago
 Lecture Slides
13:00 - 14:00 Lunch
14:00 - 16:00 ML: Looking Ahead
Jose Carlos Principe  University of Florida Gainesville
 Lecture Slides
16:00 - 16:30 Coffee Break
16:30 - 18:30 Bias in the Web - Bias on the Web
Ricardo Baeza-Yates  NTENT
 Lecture Slides
18:30 - 19:00 Opening
19:00 - 20:00 Welcome reception
Hour
9:00 - 10:45 Big Data - Distributed Learning
Gianmarco De Francisci Morales  QCRI
 Lecture Slides
10:45 - 11:00 Coffee Break
11:00 - 13:00 Probability Tools for Data Stream Processing
Ricard Gavaldà
 Lecture Slides
13:00 - 14:00 Lunch
14:00 - 16:00 Learning from Data Streams for Predictive Maintenance
João Gama
 Lecture Slides
16:00 - 16:30 Coffee Break
16:30 - 17:30 Data Quality
Pedro P. Rodrigues
 Lecture Slides
17:30 - 18:30 WATSON by IBM - Introduction to IBM Watson Studio
Roy Cecil
Jorge M Soares
 Lecture Slides
18:30 - 19:30 Banquet
Hour
9:00 - 10:45 Geographic Data Mining - Big Data for understanding human dynamics: the power of networks
Fosca Giannotti  ISTI-CNR
 Lecture Slides
10:45 - 11:00 Coffee Break
11:00 - 13:00 Data Science for nowcasting & forecasting
Dino Pedreschi  Univ of Pisa
 Lecture Slides
13:00 - 14:00 Lunch
14:00 - 16:00 Multi-dimensional Bayesian network classifiers
Pedro Larrañaga  UPM, Madrid
 Lecture Slides
16:00 - 16:30 Coffee Break
16:30 - 17:30 Network Analysis
Pedro Ribeiro  DCC/FCUP & CRACS
 Lecture Slides
17:30 - 18:15 Farfetch - Farfetch, where Fashion meets Data
João Gomes  Farfetch
18:15 - 19:00 EDP: Data Sciences Applied to Energy - Artificial Intelligence and the Energy Business – recent applications of AI at EDP
EDP Speaker
 Lecture Slides
Hour
9:00 - 10:45 Recommender Systems
Alípio Jorge  UP, INESC TEC
João Vinagre
 Lecture Slides
10:45 - 11:00 Coffee Break
11:00 - 13:00 Deep Learning & Reinforcement Learning
Olivier Pietquin  Google Brain
 Lecture Slides
13:00 - 14:00 Lunch
14:00 - 16:00 Meta Learning - Metalearning for Algorithm Selection
Pavel Brazdil  LIAAD Inesc Tec
Carlos Soares
 Lecture Slides
16:00 - 16:30 Coffee Break
16:30 - 18:30 Hands-On SAS
Ricardo Galante  SAS Institut
 Lecture Slides

Registration

Registrations include attendance of all sessions, coffee breaks, lunches and social events.

Registration fees:

  early fees after 25 May 2018
Students 250€ 300€
Appia* 350€ 400€
Industry 500€ 600€
Accompanying Person** - 200€

* Appia members and researchers
** Fee for accompanying person includes coffee breaks, lunches and social events

We have a limit on the number of registrations (70 attendees), please register early!

Payment confirmation notification will be sent to the recorded e-mail address, once payment is processed successfully.

Organization Chairs

Program Committee

Albert Bifet
Albert Bifet
LTCI
Telecom ParisTech
 
Alípio Jorge
Alípio Jorge
University of Porto
INESC TEC
 
João Gama
João Gama
University of Porto
INESC TEC
 

Local Committee

João M. Moreira
João M. Moreira
University of Porto
INESC TEC
 
Nuno Moniz
Nuno Moniz
University of Porto
INESC TEC
 
Rita P. Ribeiro
Rita P. Ribeiro
University of Porto
INESC TEC
 

Sponsor Chair

Carlos Ferreira
Carlos Ferreira
Polytechnic Inst. of Porto
INESC TEC
 

Web Chair

Nuno Moniz
Nuno Moniz
University of Porto
INESC TEC
 
Sylwia Bugla
Sylwia Bugla
University of Porto
INESC TEC
 

Partners / Sponsors

Platinum Sponsors

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Gold Sponsors

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Bronze Sponsors

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Venue

Department of Computer Science, Faculty of Sciences, University of Porto

Rua do Campo Alegre 1021/1055
4169-007 Porto, Portugal
+351 220 402 900

Google Maps coordinates: 41.1522135,-8.6424578

How to get to the venue with public transportation

  • By subway: the nearest subway station is "Casa da Música" (lines A, B, C and E) at a walking distance of about 15m. For more information see the official page: "Metro do Porto" (system map in PDF)
  • By bus: the nearest bus stop is "Casa das Artes", served by four different regular lines: 200, 204, 207 and 504. This stop is right in front of the venue. For more information see the official page: STCP - Porto Public Bus (lines map)
  • By train: Porto's main train stations are "S. Bento" and "Campanhã". Both are served by subway stations. Line 207 also passes through both train stations and the bus stop at the venue.

Contacts

Workshop Organization

General Email
eaia2018@dcc.fc.up.pt