DSM 2020 : FIRST INTERNATIONAL SUMMER SCHOOL ON DATA SCIENCE FOR MOBILITY
Call For Papers
FIRST INTERNATIONAL SUMMER SCHOOL ON DATA SCIENCE FOR MOBILITY
April 27 - May 1, 2020
Kastelli Resort, Kamari Village, Santorini, Greece
*** EXTENDED DEADLINE ***
Due to the many requests, the deadline for submitting the application form is extended to March 13, 2020
*** Call for Participation ***
Massive amounts of Spatio-temporal data representing trajectories of moving objects are produced by an ever-increasing number of diverse, real-life applications, ranging from mobile to social media apps and surveillance systems, from vehicle tracking systems to IoT mobile sensors. Such mobility-aware traces come in huge numbers and very complex forms and can be enriched with multiple different semantic dimensions. These semantically enriched trajectories have the potential to unveil novel challenges in several domains, such as urban, maritime and aviation.
The explosion in Data Science is happening now. The Big Data technological infrastructure has reached maturity. Significant interest from the research community is being shown towards the Big Data Value Analytics reference model: data management, data processing, data analytics, data visualization. The time is right for the field of Mobility Data Science to follow the trend!
Our First Summer School on Data Science for Mobility offers participants both visionary keynote speeches and hands-on mini-courses held by leading experts in AI and Data Analytics for Mobility from Canada, Greece & Italy. The keynotes speeches will explore the challenges faced due to the voluminous and complex mobility data generated every day in maritime and aviation domains. The hands-on mini-courses complement the keynotes by giving practical experience in the usage of analysis tools on real mobility datasets.
This Summer School is intended for PhD students, researchers and practitioners in the fields of Computer and Information Science, interested in learning about the most recent developments in mobility data science. Attendees will familiarise themselves with the most recent data science trends, including deep learning and AI methods for mobility data, methods to analyze human mobility as well as with methods for big mobility data. With the hands-on experience, participants will gain familiarity with some commonly used tools and datasets.
At the end of the course, each attendee will:
** Understand how to analyze mobility data with deep learning techniques
** Understand how machine learning and AI methods can be tailored to mobility data
** Understand how to manage Big Mobility Data
** Gain significant hands-on experience with state-of-the-art technologies and tools
** Have a vision of open research as well as technological challenges customized to key application areas and domains
Prof. Stan Matwin, Dalhousie University (Canada)
Title of the talk: Maritime applications of Machine Learning
Prof. George Vouros, University of Piraeus (Greece)
Title of the talk: Planning the path: an aviation perspective
HANDS-ON MINI COURSES
Title: Deep Learning for Mobility
Tutors: Claudio Lucchese (University Ca' Foscari Venice, Italy) & Vinicius Cesar Monteiro de Lira (ISTI-CNR, Italy)
Title: Human mobility analysis and simulation in Python
Tutors: Luca Pappalardo (ISTI-CNR, Italy)
Title: Learning from our movements: Big Mobility Data Analytics
Tutors: Yannis Theodoridis (Data Science Lab, University of Piraeus, Greece) & Panagiotis Tampakis (Data Science Lab, University of Piraeus, Greece)
PANEL: Emerging issues on mobility data science
The objective of this panel session is to highlight the emerging issues that relate to the analysis of mobility data and their applications. Examples of such issues could revolve around: datasets, AI approaches, privacy compromise, unethical use of analysis products and others. The audience will get the chance to participate in a live discussion with experts in the field from academia and industry, who will share their opinions, in a moderated open discussion.
Prof. Stan Matwin (Dalhousie University, Canada)
Prof. Bettina Berendt (Leuven University, Belgium)
Prof. Claudio Lucchese (University Ca’ Foscari Venice, Italy)
Luca Pappalardo (National Research Council, Italy)
Prof. Yannis Theodoridis (University of Piraeus, Greece)
Fabrizio Silvestri (Facebook London, UK)
Moderator: Konstantinos Tserpes (Harokopio University, Greece)
Registration deadline is FEBRUARY 28, 2020.
Registration fee is 300 euro.
Details on the registration procedure and the school schedule are available at the school web site: http://master-school.isti.cnr.it
The Data Science for Mobility school is happy to offer a limited number of travel grants of maximum 500 euro to facilitate the students participation.
The scholarships will be selected by the DSM scientific committee and offered to those registered students who submitted an application and are preferentially coming from outside Europe with priority to the MASTER project partners.
How to apply:
Register to the school following the instructions at the school website: http://master-school.isti.cnr.it.
Send a motivation letter, your CV, your DSM registration receipt and your student status proof (e.g. a certificate) to firstname.lastname@example.org before 15 of March 2020.
The selected applicants will be notified by e-mail within 7 days from the deadline and they will receive the scholarship after the school by bank transfer upon presentation of receipts of expenses .
The Summer School will be held at the Kastelli Resort on the magic island of Santorini, in Greece.
The Summer School has a limited number of rooms reserved at a special rate in the hotels below. All the participants are warmly invited to reserve their accommodation as soon as possible.
*** Kastelli Resort, the venue of the Summer School, is a peaceful luxury retreat that combines an idyllic and convenient location, with upscale accommodation, state-of-the-art facilities, and impeccable services.
*** Dioskouri Art Villas is a 3* boutique hotel situated in a central and quiet area of the village Kamari in Santorini, near Kamari Beach. The hotel is two minutes walking from the venue of the summer school.
For details on how to book please check instructions at: http://master-school.isti.cnr.it/accomodation/
The Data Science for Mobility school offers a rich social program, including a Welcome cocktail with dinner on Monday 27th, the trip to Oia to admire the famous Santorini sunset on Wednesday April 29, and a wine tasting experience with the Caldera view on Friday May 1st. All details are available at: http://master-school.isti.cnr.it/social-program/
University of Piraeus (Greece)
Konstantinos Tserpes (Harokopio University, Greece)
Karine Zeitouni (University of Versailles Saint Quentin, France)
Jose Fernandes da Macedo (Federal University of Ceara’, Brazil)
Amilcar Soares (Dalhousie University, Canada)
Alessandra Raffaeta’ (University Ca’ Foscari of Venice, Italy)
Yannis Theodoridis (University of Piraeus, Greece)
Raffaele Perego (ISTI-CNR, Italy)
Lorenzo Gabrielli (ISTI-CNR, Italy)
Beatrice Rapisarda (IIT-CNR, Italy)
This Summer School is supported and organized by H2020 MSCA project MASTER GA 777695 http://www.master-project.h2020.eu
Sponsored by H2020 project Track and Know GA 780754 https://trackandknowproject.eu
For further information: master-summer-chairs AT isti.cnr.it