Sunday, March 5, 2023

[DMANET] BigDat 2023 Summer: early registration March 7



BigDat 2023 Summer

Las Palmas de Gran Canaria, Spain

July 17-21, 2023


Co-organized by:

University of Las Palmas de Gran Canaria

Institute for Research Development, Training and Advice - IRDTA


Early registration: March 7, 2023



BigDat 2023 Summer is part of a multi-event called Deep&Big 2023 consisting=
also of DeepLearn 2023 Summer. BigDat 2023 Summer participants will have t=
he opportunity to attend lectures in the program of DeepLearn 2023 Summer a=
s well if they are interested.


BigDat 2023 Summer will be a research training event with a global scope ai=
ming at updating participants on the most recent advances in the critical a=
nd 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 res=
earch and industrial innovation with an extraordinary potential for a huge =
impact on scientific discoveries, health, 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, infrastructur=
e, management, search and mining, analytics, security and privacy, as well =
as applications to biology and medicine, business, finance, transportation,=
online social networks, etc. Major challenges of analytics, management and=
storage of big data will be identified through 14 four-hour and a half cou=
rses and 2 keynote lectures, which will tackle the most active and promisin=
g topics. The organizers are convinced that outstanding speakers will attra=
ct the brightest and most motivated students. Face to face interaction and =
networking will be main ingredients of the event. It will be also possible =
to fully participate in vivo remotely.

An open session will give participants the opportunity to present their own=
work in progress in 5 minutes. Moreover, there will be two special session=
s with industrial and employment profiles.


Graduate students, postgraduate students and industry practitioners will be=
typical profiles of participants. However, there are no formal pre-requisi=
tes for attendance in terms of academic degrees, so people less or more adv=
anced in their career will be welcome as well. Since there will be a variet=
y of levels, specific knowledge background may be assumed for some of the c=
ourses. Overall, BigDat 2023 Summer is addressed to students, researchers a=
nd practitioners who want to keep themselves updated about recent developme=
nts and future trends. All will surely find it fruitful to listen to and di=
scuss with major researchers, industry leaders and innovators.


BigDat 2023 Summer will take place in Las Palmas de Gran Canaria, on the At=
lantic Ocean, with a mild climate throughout the year, sandy beaches and a =
renowned carnival. The venue will be:

Instituci=C3=B3n Ferial de Canarias
Avenida de la Feria, 1
35012 Las Palmas de Gran Canaria


2 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 f=
rom one to another.

Also, if interested, participants will be able to attend courses developed =
in DeepLearn 2023 Summer, which will be held in parallel and at the same ve=

Full live online participation will be possible. The organizers highlight, =
however, the importance of face to face interaction and networking in this =
kind of research training event.


Valerie Daggett (University of Washington), Dynameomics: From Atomistic Sim=
ulations of All Protein Folds to the Discovery of a New Protein Structure t=
o the Design of a Diagnostic Test for Alzheimer=E2=80=99s Disease

Sander Klous (University of Amsterdam), How to Audit an Analysis on a Feder=
ative Data Exchange


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

Marcelo Bertalm=C3=ADo (Spanish National Research Council), [introductory] =
The Standard Model of Vision and Its Limitations: Implications for Imaging,=
Vision Science and Artificial Neural Networks

Gianluca Bontempi (Universit=C3=A9 Libre de Bruxelles), [intermediate/advan=
ced] Big Data Analytics in Fraud Detection and Churn Prevention: from Predi=
ction to Causal Inference

Altan =C3=87akir (Istanbul Technical University), [introductory/intermediat=
e] Introduction to Distributed Deep Learning with Apache Spark

Ian Fisk (Flatiron Institute), [introductory] Setting Up a Facility for Dat=
a Intensive Science Analysis

Ravi Kumar (Google), [intermediate/advanced] Differential Privacy

Wladek Minor (University of Virginia), [introductory/advanced] Big Data in =
Biomedical Sciences

Jos=C3=A9 M.F. Moura (Carnegie Mellon University), [introductory/intermedia=
te] Graph Signal Processing and Geometric Learning

Panos Pardalos (University of Florida), [intermediate/advanced] Data Analyt=
ics for Massive Networks

Ramesh Sharda (Oklahoma State University), [introductory/intermediate] Netw=
ork-Based Health Analytics

Steven Skiena (Stony Brook University), [introductory/intermediate] Word an=
d Graph Embeddings for Machine Learning

Mayte Suarez-Farinas (Icahn School of Medicine at Mount Sinai), [intermedia=
te] Meta-Analysis Methods for High-Dimensional Data

Ana Trisovic (Harvard University), [introductory/advanced] Reproducible Res=
earch, Best Practices and Big Data Management

Sebasti=C3=A1n Ventura (University of C=C3=B3rdoba), [intermediate] Supervi=
sed Descriptive Pattern Mining


An open session will collect 5-minute voluntary presentations of work in pr=
ogress by participants. They should submit a half-page abstract containing =
the title, authors, and summary of the research to by July 9=
, 2023.


A session will be devoted to 10-minute demonstrations of practical applicat=
ions of big data in industry. Companies interested in contributing are welc=
ome to submit a 1-page abstract containing the program of the demonstration=
and the logistics needed. People in charge of the demonstration must regis=
ter for the event. Expressions of interest have to be submitted to david@ir= by July 9, 2023.


Organizations 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-pa=
ge .pdf leaflet with a brief description of the organization and the profil=
es looked for to be circulated among the participants prior to the event. P=
eople in charge of the search must register for the event. Expressions of i=
nterest have to be submitted to by July 9, 2023.


Carlos Mart=C3=ADn-Vide (Tarragona, program chair)
Sara Morales (Brussels)
David Silva (London, organization chair)


It has to be done at

The selection of 8 courses requested in the registration template is only t=
entative 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 as well as=
eventually courses in DeepLearn 2023 Summer.

Since the capacity of the venue is limited, registration requests will be p=
rocessed on a first come first served basis. The registration period will b=
e closed and the on-line registration tool disabled when the capacity of th=
e venue will have got exhausted. It is highly recommended to register prior=
to the event.


Fees comprise access to all courses and lunches. There are several early re=
gistration deadlines. Fees depend on the registration deadline.

The fees for on site and for online participation are the same.


Accommodation suggestions will be available in due time at


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

Participants will be recognized 2 ECTS credits by University of Las Palmas =
de Gran Canaria.



Cabildo de Gran Canaria

Universidad de Las Palmas de Gran Canaria - Fundaci=C3=B3n Parque Cient=C3=
=ADfico Tecnol=C3=B3gico

Universitat Rovira i Virgili

Institute for Research Development, Training and Advice =E2=80=93 IRDTA, Br=
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