-------- Forwarded Message --------
BigDat 2019: early registration October 15
*To be removed from our mailing list, please respond to this
message with UNSUBSCRIBE in the subject line*
********************************************************
5th INTERNATIONAL WINTER SCHOOL ON BIG DATA
BigDat 2019
Cambridge, United Kingdom
January 7-11, 2019
Co-organized by:
Cambridge Big Data Initiative, University of Cambridge
Institute for Research Development, Training and Advice (IRDTA)
Brussels / London
http://bigdat2019.irdta.eu/
********************************************************
--- Early registration deadline: October 15, 2018 ---
********************************************************
SCOPE:
BigDat 2019 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 2 keynote lectures, 24
four-hour 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. 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 2019 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 2019 will take place in Cambridge, a city home of a
world-renowned university. The venue will be:
University of Cambridge
Department of Engineering
Trumpington Street
Cambridge CB2 1PZ
KEYNOTE SPEAKERS:
tba
PROFESSORS AND COURSES:
Thomas Bäck (Leiden University), [introductory/intermediate], Data
Driven Modeling and Optimization for Industrial Applications
Richard Bonneau (New York University), [introductory] Large Scale
Machine Learning Methods for Integrating Protein Sequence and
Structure to Predict Gene Function
Altan Cakir (Istanbul Technical University),
[introductory/intermediate] Processing Big Data with Apache Spark:
From Science to Industrial Applications
Jiannong Cao (Hong Kong Polytechnic University),
[introductory/intermediate] Cross-domain Big Data Fusion and
Analytics
Nitesh Chawla (University of Notre Dame), [intermediate/advanced]
Network Science: Representation Learning and Higher Order Networks
Nello Cristianini (University of Bristol), [introductory] The
Interface between Big Data and Society
Geoffrey C. Fox (Indiana University, Bloomington), [intermediate]
High Performance Big Data Computing
David Gerbing (Portland State University), [introductory] Data
Visualization with R
Craig Knoblock (University of Southern California),
[intermediate/advanced] Building Knowledge Graphs
Geoff McLachlan (University of Queensland),
[intermediate/advanced] Applying Finite Mixture Models to Big Data
Folker Meyer (Argonne National Laboratory), [intermediate]
Skyport2: A Multi Cloud Framework for Executing Scientific
Workflows
Wladek Minor (University of Virginia), [introductory/advanced] Big
Data in Biomedical Sciences
Soumya Mohanty (University of Texas Rio Grande Valley),
[introductory/intermediate] Swarm Intelligence Methods for
Statistical Regression
Sankar K. Pal (Indian Statistical Institute),
[introductory/advanced] Machine Intelligence and Soft Granular
Mining: Features, Applications and Challenges
Lior Rokach (Ben-Gurion University of the Negev),
[introductory/advanced] Ensemble Learning
Michael Rosenblum (University of Potsdam),
[introductory/intermediate] Synchronization Approach to Time
Series Analysis
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), [intermediate/advanced]
Statistical Inference: Optimal Methods for Learning from Signals
in Noise
Jaideep Srivastava (University of Minnesota), [intermediate]
Social Computing – Concepts and Applications
Mayte Suárez-Fariñas (Icahn School of Medicine at Mount Sinai),
[intermediate] A Practical Guide to the Analysis of Longitudinal
Data Using R
Jeffrey Ullman (Stanford University), [introductory] Big-data
Algorithms That Aren't Machine Learning
Andrey Ustyuzhanin (National Research University Higher School of
Economics), [intermediate/advanced] Surrogate Modelling for Fun
and Profit
Wil van der Aalst (RWTH Aachen University),
[introductory/intermediate] Process Mining: Data Science in Action
Zhongfei Zhang (Binghamton University), [introductory/advanced]
Relational and Multimedia Data Learning
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 December 30, 2018.
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. At
least one of the people participating in the demonstration must
register for the event. Expressions of interest have to be
submitted to
david@irdta.eu by December 30, 2018.
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. At least one of the people in
charge of the search must register for the event. Expressions of
interest have to be submitted to
david@irdta.eu by December 30,
2018.
ORGANIZING COMMITTEE: (to be completed)
Sara Morales (Brussels)
Manuel J. Parra-Royón (Granada)
David Silva (London, co-chair)
Filippo Spiga (Cambridge, co-chair)
Richard E. Turner (Cambridge)
REGISTRATION:
It has to be done at
http://bigdat2019.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 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 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 on the event website.
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:
Cambridge Big Data Initiative, University of Cambridge
Institute for Research Development, Training and Advice (IRDTA) –
Brussels/London