BigDat 2017: una Winter School a Bari sui BIG DATA

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BigDat 2017 è una Winter School che si svolgerà a Bari, presso il Dipartimento di Informatica, dal 13 al 17 Febbraio 2017.

Per la prima volta la scuola, giunta alla sua terza edizione, farà tappa in Italia. I più importanti specialisti al mondo sui Big Data si incontreranno per dar vita ad un appuntamento unico e imperdibile.

La scuola è rivolta principalmente a laureati, studenti di dottorato e postdoc di tutto il mondo, tuttavia non ci sono vincoli formali in termini di requisiti accademici per l’iscrizione. La scuola è anche indicata per figure senior che vogliono rimanere aggiornate sui trend futuri dei Big Data, manager di aziende tecnologiche, ricercatori e innovatori.

Tutti i corsi saranno tenuti in lingua inglese.

Per maggiori informazioni e per procedere alle iscrizioni si può andare sul sito web istituzionale cliccando qui.

Professors and Courses

Thomas Bäck (Leiden University), [introductory/intermediate] Data Analytics and Optimization for Mobdro APK Industrial Applications: Introduction, Algorithms, and Examples

Paul Bliese (University of South Carolina), [introductory/intermediate] Using R for Mixed-effects (Multilevel) Models

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

Tamás Budavári (Johns Hopkins University), [introductory] Big Data Approaches in Astronomy

Diego Calvanese (Free University of Bozen-Bolzano), [advanced] Data-aware Processes: Modeling and Verification

Amr El Abbadi (University of California, Santa Barbara), [introductory/intermediate] Managing Big Data in the Cloud

Geoffrey C. Fox (Indiana University), [intermediate] Using High Performance Computing for Big Data Analytics

Minos Garofalakis (Technical University of Crete), [intermediate/advanced] Streaming Big Data Analytics

David W. Gerbing (Portland State University), [introductory] Data Visualization with R

Georgios B. Giannakis (University of Minnesota), [advanced] Signal Processing Tools for Big Data Analytics

Sander Klous(University of Amsterdam), [introductory] We Are Big Data

Laks V.S. Lakshmanan (University of British Columbia), [introductory] Analysis of Large Social Networks

Maurizio Lenzerini (Sapienza University of Rome), [intermediate/advanced] Ontology-based Data Management

Soumya D. Mohanty (University of Texas Rio Grande Valley), [introductory/intermediate] Swarm Intelligence Methods and Optimization Problems in Big Data Analytics

Bernhard Pfahringer (University of Waikato), [introductory] Introduction to Data Stream Mining for Big Data

Krithi Ramamritham (Indian Institute of Technology Bombay), [introductory/intermediate] Harnessing Big Mobdro APK Data for Building Smart Things

Michael Rosenblum (University of Potsdam), [introductory/intermediate] Coupled Oscillators Approach in Time Series Analysis

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

V.S. Subrahmanian (University of Maryland), [introductory/intermediate] Big Data in Cybersecurity

Alexander S. Tuzhilin (New York University), [introductory/intermediate] Recommender Systems and Big Data

Jeffrey Ullman (Stanford University), [introductory] Big Data Algorithms that Aren’t Machine Learning

Lyle Ungar (University of Pennsylvania), [introductory] Sentiment Mining from User Generated Content

John Wright (Columbia University), [intermediate/advanced] Sparse and Low-Dimensional Models for High-Dimensional Data: Theory, Algorithms and Applications

Zhongfei Zhang (Binghamton University), [introductory/advanced] Knowledge Discovery from Relational and Multimedia Data