International Winter School on Big Data

Tarragona, Spain, January 26-30, 2015

BigDat 2015 Registration Form

(form version 1.11 courses)


  1. Either by bank transfer to:

    Uno-e Bank
    bank's address: Julian Camarillo 4 C, 28037 Madrid, Spain
    IBAN: ES3902270001820201823142
    account holder: C. Martin – GRLMC
    account holder’s address: Av. Catalunya 35, 43002 Tarragona, Spain

  2. Remarks: (1) Bank transfers should not involve any expense for the School. (2) Participants claiming early registration will be requested to prove that the bank transfer order was carried out by the deadline in case the fees arrive later.

  3. Or by PayPal.

  4. Remark: An extra fee of Euro 25 will be added automatically, to cover the transfer expenses PayPal will charge to the organizers.

General remarks concerning payment:
  • Please mention BigDat 2015 and your name in the subject.
  • A receipt will be provided on site.
  • Participants registering on site must pay in cash. For the sake of local organization, however, it is much recommended to do it earlier.


Fees comprise access to all courses and lunches.

Registration deadlines and fees

Paid until Full [Euro]
June 23, 2014290
July 23, 2014330
August 23, 2014370
September 23, 2014410
October 23, 2014450
November 23, 2014490
December 23, 2014530
January 23, 2015570
January 30, 2015610

Registration conditions

Please provide the following contact information: (bold fields are mandatory)!

1 The default values for City and Country fields are based on the client IP remote address. This information might be not very accurate (due to ISP policies, proxy connections, etc.), and we kindly ask you to provide the right values for the registration form.


Name in Latex:
(with accents, please)



(Professor, Researcher, PhD student, etc.)




Please provide the following academic background:

Degree (PhD, Masters, Bachelor, etc.):


Speciality (if any):

Registration Type: 610 Euro
Please indicate maximum 8 courses you would tentatively like to attend.

Hendrik Blockeel (KU Leuven), [intermediate] Decision Trees for Big Data Analytics

Diego Calvanese (Free University of Bozen-Bolzano), [introductory/intermediate] End-User Access to Big Data Using Ontologies

Jiannong Cao (Hong Kong Polytechnic University), [introductory/intermediate] Programming with Big Data

Edward Y. Chang (HTC Corporation, New Taipei City), [introductory/advanced] Big Data Analytics: Architectures, Algorithms, and Applications

Ernesto Damiani (University of Milan and Etisalat British Telecom Innovation Center, Abu Dhabi), [introductory/intermediate] Process Discovery and Predictive Decision Making from Big Data Sets and Streams

Gautam Das (University of Texas Arlington), [intermediate/advanced] Mining Deep Web Repositories

Geoffrey C. Fox (Indiana University, Bloomington), [intermediate] Using Software Defined Systems to Address Big Data Problems

Minos Garofalakis (Technical University of Crete, Chania) [intermediate/advanced], Querying Continuous Data Streams

Kwan-Liu Ma (University of California Davis), [intermediate] Big Data Visualization

Christoph Meinel (Hasso Plattner Institute, Potsdam), [introductory/intermediate] New Computing Power by In-Memory and Multicore to Tackle Big Data

Manish Parashar (Rutgers University, Piscataway), [intermediate] Big Data Challenges in Simulation-based Science

Srinivasan Parthasarathy (Ohio State University, Columbus), [intermediate] Scalable Data Analysis

Evaggelia Pitoura (University of Ioannina), [introductory/intermediate] Online Social Networks

Vijay V. Raghavan (University of Louisiana Lafayette), [introductory/intermediate] Visual Analytics of Time-evolving Large-scale Graphs

Pierangela Samarati (University of Milan), [intermediate], Data Security and Privacy in the Cloud

Peter Sanders (Karlsruhe Institute of Technology), [introductory/intermediate] Algorithm Engineering for Large Data Sets

Johan Suykens (KU Leuven), [introductory/intermediate] Fixed-size Kernel Models for Big Data

Domenico Talia (University of Calabria, Rende), [intermediate] Scalable Data Mining on Parallel, Distributed and Cloud Computing Systems

Jieping Ye (Arizona State University, Tempe), [introductory/advanced] Large-Scale Sparse Learning and Low Rank Modeling

Supplementary information:

Arriving Date:

Departure Date:

Notes for organizers:

Acknowledgement and Copyright Notice

To get City and Country information we use the GeoLite City databases, and the free server library provided by MaxMind (Copyright (c) 2008 MaxMind, Inc.) for which there is an OPEN DATA LICENSE.

This product includes GeoLite data created by MaxMind, available from