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BigDat 2020: early registration October 27
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6th INTERNATIONAL WINTER SCHOOL ON BIG DATA
BigDat 2020
Ancona, Italy
January 13-17, 2020
Co-organized by:
Department of Information Engineering, Marche Polytechnic
University
Institute for Research Development, Training and Advice (IRDTA)
Brussels / London
https://bigdat2020.irdta.eu/
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--- Early registration deadline: October 27, 2019 ---
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SCOPE:
BigDat 2020 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, 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 1 keynote lecture and 22
four-hour and a half courses, 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 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 2020 will take place in Ancona, a city founded by Greek
settlers and today one of the main ports on the Adriatic Sea. The
venue will be:
Department of Information Engineering
Marche Polytechnic University
Via Brecce Bianche 12
60131 Ancona
KEYNOTE SPEAKER: (to be completed)
PROFESSORS AND COURSES:
Sanchita Bhattacharya (University of California, San Francisco),
[introductory/advanced] Big Data in Immunology: Sharing,
Dissemination, and Repurposing
Diego Calvanese (Free University of Bozen-Bolzano), [introductory]
Virtual Knowledge Graphs for Data Integration
Sheelagh Carpendale (University of Calgary), [introductory] Data
Visualization
Nitesh V. Chawla (University of Notre Dame),
[intermediate/advanced] Learning from Imbalanced Data
Amr El Abbadi (University of California, Santa Barbara),
[introductory/intermediate] An Introduction to Blockchain
Charles Elkan (University of California, San Diego),
[intermediate] A Rapid Introduction to Modern Deep Learning
Minos Garofalakis (Technical University of Crete),
[intermediate/advanced] Private Data Analytics at Scale
Jiawei Han (University of Illinois, Urbana-Champaign),
[intermediate/advanced] From Unstructured Text to TextCube:
Automated Construction and Multidimensional Exploration
Xiaohua Tony Hu (Drexel University), [introductory/advanced]
Machine Learning Methods for Big Microbiome Data Analysis
Craig Knoblock (University of Southern California),
[intermediate/advanced] Building Knowledge Graphs
Wladek Minor (University of Virginia), [introductory/advanced] Big
Data in Biomedical Sciences
Bamshad Mobasher (DePaul University), [intermediate] Context-aware
Recommender Systems
Jayanti Prasad (Embold Technologies), [introductory/intermediate]
Big Code
Lior Rokach and Bracha Shapira (Ben-Gurion University of the
Negev), [introductory/intermediate] Recommender Systems
Peter Rousseeuw (KU Leuven), [introductory] Anomaly Detection by
Robust Methods
Asim Roy (Arizona State University), [intermediate] Hardware-based
(GPU, FPGA based) Machine Learning That Exploits Massively
Parallel Computing – An Overview of Concepts, Architectures and
Neural Network Algorithm Implementation
Hanan Samet (University of Maryland), [introductory/intermediate]
Sorting in Space: Multidimensional, Spatial, and Metric Data
Structures for Applications in Spatial and Spatio-textual
Databases, Geographic Information Systems (GIS), and
Location-based Services
Rory Smith (Monash University), [introductory/intermediate]
Learning from Data, the Bayesian Way
Jaideep Srivastava (University of Minnesota),
[introductory/intermediate] Social Computing
Mayte Suárez-Fariñas (Icahn School of Medicine at Mount Sinai),
[intermediate/advanced] Meta-analysis Methods for High-dimensional
Data
Jeffrey Ullman (Stanford University), [introductory] Big-data
Algorithms That Aren't Machine Learning
Wil van der Aalst (RWTH Aachen University),
[introductory/intermediate] Process Mining: A Very Different Kind
of Machine Learning That Can Be Applied in Any Organization
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@irdta.eu by January 5, 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@irdta.eu by
January 5, 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@irdta.eu by January 5, 2020.
ORGANIZING COMMITTEE:
Emanuele Frontoni (Ancona, co-chair)
Sara Morales (Brussels)
Manuel J. Parra-Royón (Granada)
David Silva (London, co-chair)
Flavio Tonetto (Ancona, industrial chair)
Domenico Ursino (Ancona, co-chair)
REGISTRATION:
It has to be done at
https://bigdat2020.irdta.eu/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
facility 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.
ACCOMMODATION:
Suggestions for accommodation are available at
https://bigdat2020.irdta.eu/accommodation/
CERTIFICATE:
A certificate of successful participation in the event will be
delivered indicating the number of hours of lectures.
QUESTIONS AND FURTHER INFORMATION:
david@irdta.eu
ACKNOWLEDGMENTS:
Dipartimento di Ingegneria dell'Informazione, Università
Politecnica delle Marche
Institute for Research Development, Training and Advice (IRDTA) –
Brussels/London
CONFINDUSTRIA Marche Nord
CINI AIIS National Lab