[Om-announce] BigDat 2020 Autumn: early registration June 2

IRDTA irdta at irdta.eu
Sun May 24 23:58:36 CEST 2020


BigDat 2020 Autumn: early registration June 2*To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line*


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7th INTERNATIONAL SCHOOL ON BIG DATA


BigDat 2020 Autumn


Beersheba, Israel


October 25-29, 2020


Co-organized by:


Ben-Gurion University of the Negev

Department of Software and Information Systems Engineering

Data Science Research Center


Institute for Research Development, Training and Advice (IRDTA)

Brussels / London


https://irdta.eu/bigdat2020a/


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--- Early registration deadline: June 2, 2020 ---


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SCOPE:


BigDat 2020 Autumn will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of big data. Previous events were held in Tarragona, Bilbao, Bari, Timisoara, Cambridge and Ancona.


Big data is a broad field covering 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 24 four-hour and a half courses, 2 keynote lectures 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. Moreover, there will be two special sessions with industrial and recruitment profiles.


ADDRESSED TO:


Master's 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 2020 Autumn 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.


VENUE:


BigDat 2020 Autumn will take place in Beersheba, the largest city in the Negev desert of southern Israel and an important technology center. The venue will be:


Ben-Gurion University of the Negev

Marcus Family Campus


https://in.bgu.ac.il/en/Pages/interactive.aspx


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.


KEYNOTE SPEAKERS:


tba


PROFESSORS AND COURSES: (to be completed)


Paolo Addesso (University of Salerno), [introductory/intermediate] Data Fusion for Remotely Sensed Data


Thomas Bäck & Hao Wang (Leiden University), [introductory/intermediate] Data Driven Modeling and Optimization for Industrial Applications


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


Altan Cakir (Istanbul Technical University), [intermediate] Big Data Analytics with Apache Spark


Edward Chang (Stanford University), [intermediate] Artificial Intelligence for Disease Diagnosis and Precision Surgery


Michael X. Cohen (Radboud University Nijmegen), [introductory] Dimension Explosion and Dimension Reduction in Brain Electrical Activity


Ian Fisk (Flatiron Institute), [introductory] The Infrastructure to Support Data Science


Michael Freeman (University of Washington), [intermediate] Interactive Data Visualization Using D3 + Observable


David Gerbing (Portland State University), [introductory] Derive Meaning from Data with R Visualizations


Yifan Hu (Yahoo Research), [introductory/advanced] Data Visualization and Machine Learning


Wagner A. Kamakura (Rice University), [intermediate] Advanced Business Analytics using Excel Addins


Ravi Kumar (Google), [intermediate/advanced] Clustering for Big Data


Victor O.K. Li (University of Hong Kong), [intermediate] Deep Learning and Applications


Panos Pardalos (University of Florida), [intermediate/advanced] Optimization and Data Sciences Techniques for Large Networks


Valeriu Predoi (University of Reading), [introductory] A Beginner's Guide to Big Data Analysis: How to Connect Scientific Software Development with Real World Problems


Alexandre Vaniachine (VirtualHealth), [intermediate] Open-source Columnar Databases


Sebastián Ventura (University of Córdoba), [intermediate/advanced] Supervised Descriptive Pattern Mining


Xiaowei Xu (University of Arkansas, Little Rock), [introductory/advanced] Deep Learning for Text Mining


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 the title, authors, and summary of the research to david at irdta.eu by October 17, 2020.


INDUSTRIAL SESSION:


A session will be devoted to 10-minute 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 and the logistics needed. People participating in the demonstration must register for the event. Expressions of interest have to be submitted to david at irdta.eu by October 17, 2020.


EMPLOYER SESSION:


Firms searching for personnel well skilled in big data will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the company and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david at irdta.eu by October 17, 2020.


ORGANIZING COMMITTEE:


Stavi Baram (Beersheba)

Mark Last (Beersheba)

Carlos Martín-Vide (Tarragona, program chair)

Sara Morales (Brussels)

Manuel J. Parra-Royón (Granada)

Lior Rokach (Beersheba, co-chair)

Bracha Shapira (Beersheba, co-chair)

David Silva (London, co-chair)


REGISTRATION:


It has to be done at


https://irdta.eu/bigdat2020a/registration/


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 estimation 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 tool disabled when 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.


Refunding of registration fees will not be possible. However, an exception will be made in case the event must be postponed due to the continuation of the coronavirus crisis in Autumn (which is a scenario the organizers do not expect).


ACCOMMODATION:


Suggestions for accommodation will be available in due time.


CERTIFICATE:


A certificate of successful participation in the event will be delivered indicating the number of hours of lectures.


QUESTIONS AND FURTHER INFORMATION:


david at irdta.eu


ACKNOWLEDGMENTS:


Ben-Gurion University of the Negev


Institute for Research Development, Training and Advice (IRDTA) – Brussels/London
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