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ISCApad Archive  »  2017  »  ISCApad #234  »  Events  »  Other Events  »  (2018-01-22) 4th INTERNATIONAL WINTER SCHOOL ON BIG DATA, BigDat 2018, Timisoara, Romania

ISCApad #234

Monday, December 11, 2017 by Chris Wellekens

3-3-15 (2018-01-22) 4th INTERNATIONAL WINTER SCHOOL ON BIG DATA, BigDat 2018, Timisoara, Romania
  

4th INTERNATIONAL WINTER SCHOOL ON BIG DATA
 
BigDat 2018
 
Timisoara, Romania
 
January 22-26, 2018
 
Organized by:
West University of Timisoara
Rovira i Virgili University
 
http://grammars.grlmc.com/BigDat2018/
 
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--- Early registration deadline: November 11, 2017 ---
 
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SCOPE:
 
BigDat 2018 will be a research training event with a global scope aiming at updating participants about the most recent advances in the critical and fast developing area of big data, which covers a large spectrum of current exciting research and industrial innovation with an extraordinary potential for a huge impact on scientific discoveries, medicine, engineering, business models, and society itself. Renowned academics and industry pioneers will lecture and share their views with the audience.
 
Most big data subareas will be displayed, namely foundations, infrastructure, management, search and mining, security and privacy, and applications (to biological and health sciences, to business, finance and transportation, to online social networks, etc.). Major challenges of analytics, management and storage of big data will be identified through 2 keynote lectures, 25 five-hour and fifteen-minute courses, and 1 round table, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Interaction will be a main component of the event.
 
An open session will give participants the opportunity to present their own work in progress in 5 minutes. Also, there will be two special sessions with industrial and recruitment profiles.
 
ADDRESSED TO:
 
Master students, PhD students, postdocs, and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, BigDat 2018 is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen and discuss with major researchers, industry leaders and innovators.
 
STRUCTURE:
 
3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.
 
VENUE:
 
BigDat 2018 will take place in Timi?oara, which has been nominated one of the European Capitals of Culture in 2021. The venue will be:
 
Universitatea de Vest
Blvd. Vasile Parvân, nr. 4
300223 Timi?oara
 
KEYNOTE SPEAKERS: (to be completed)
 
tba
 
PROFESSORS AND COURSES:
 
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
 
Diego Calvanese (Free University of Bozen-Bolzano), [intermediate] tba
 
Nick Duffield (Texas A&M University), [introductory/intermediate] Sampling for Big Data
 
Sa?o D?eroski (Jo?ef Stefan Institute), [introductory/intermediate] Multi-target Prediction: Techniques and Applications
 
Geoffrey C. Fox (Indiana University, Bloomington), [intermediate] Integration of HPC, Big Data Analytics and Software Ecosystem
 
Minos Garofalakis (Technical University of Crete), [intermediate/advanced] Data Streaming Analytics
 
David W. Gerbing (Portland State University), [introductory] Data Visualization with R
 
Maurizio Lenzerini (Sapienza University of Rome), [intermediate/advanced] Semantic Technologies for Open Data Publishing
 
Bing Liu (University of Illinois, Chicago), [intermediate/advanced] Lifelong Learning and its Applications in NLP
 
B.S. Manjunath (University of California, Santa Barbara), [introductory] Unstructured (Big) Data
 
Folker Meyer (Argonne National Laboratory), [introductory/intermediate] Efficient Multi Cloud Execution of Reproducible Data Analytics using Common Workflow Language, AWE and SHOCK
 
Wladek Minor (University of Virginia), [introductory/advanced] Big Data in Biomedical Sciences
 
Fionn Murtagh (University of Huddersfield), [introductory/advanced] The New Science of Big Data Analytics, Based on the Geometry and the Topology of Complex, Hierarchic Systems
 
Raymond Ng (University of British Columbia), [introductory] Mining and Summarizing Text Conversations
 
Srinivasan Parthasarathy (Ohio State University), [introductory/intermediate] Network Science Fundamentals
 
Hanan Samet (University of Maryland, College Park), [introductory/intermediate] Sorting in Space: Multidimensional, Spatial, and Metric Data Structures for Applications in Spatial Databases, Geographic Information Systems (GIS), and Location-based Services
 
Kyuseok Shim (Seoul National University), [introductory/intermediate] MapReduce Algorithms for Big Data Analysis
 
Jaideep Srivastava (Qatar Computing Research Institute), [introductory/intermediate] Social Computing
 
Jeffrey Ullman (Stanford University), [introductory] Big-data Algorithms That Aren't Machine Learning
 
Pascal Van Hentenryck (University of Michigan, Ann Arbor), [intermediate] Big Data in Transportation and Mobility
 
Sebastián Ventura (University of Córdoba), [intermediate/advanced] Pattern Mining on Big Data
 
Haixun Wang (Facebook), [intermediate/advanced] Understanding Natural Language: End-to-end and Structure Learning Approaches
 
Xiaowei Xu (University of Arkansas, Little Rock), [introductory/advanced] Mining Big Networked Data
 
Zhongfei Zhang (Binghamton University), [introductory/advanced] Relational and Media Data Learning and Knowledge Discovery
 
OPEN SESSION
 
An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing title, authors, and summary of the research to david.silva409 (at) yahoo.com by January 15, 2018.
 
INDUSTRIAL SESSION:
 
A session will be devoted to demonstrations of practical applications of big data in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration, the duration requested and the logistics necessary. At least one of the people participating in the demonstration should have registered for the event. Expressions of interest have to be submitted to david.silva409 (at) yahoo.com by January 15, 2018.
 
EMPLOYER SESSION:
 
Firms searching for personnel well skilled in big data will have a space reserved for one-to-one contacts. At least one of the people in charge of the search should have registered for the event. Expressions of interest have to be submitted to david.silva409 (at) yahoo.com by January 15, 2018.
 
ORGANIZING COMMITTEE:
 
Carlos Martín-Vide (co-chair)
Viorel Negru
Manuel J. Parra Royón
Dana Petcu
Monica Sancira (co-chair)
David Silva
 
REGISTRATION:
 
It has to be done at
 
http://grammars.grlmc.com/BigDat2018/registration.php
 
The selection of up to 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, it will be helpful to have an approximation of the respective demand for each course. During the event, participants will be free to attend the courses they wish.
 
Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration facility disabled if the capacity of the venue is exhausted. It is highly recommended to register prior to the event.
 
FEES:
 
Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline.
 
ACCOMMODATION:
 
Suggestions for accommodation will be available in due time.
 
CERTIFICATE:
 
Participants will be delivered a certificate of attendance indicating the number of hours of lectures.
 
QUESTIONS AND FURTHER INFORMATION:
 
david.silva409 (at) yahoo.com
 
ACKNOWLEDGMENTS:
 
Universitatea de Vest din Timisoara
Universitat Rovira i Virgili4th


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