April 27 – May 1, 2020
Kastelli Resort, Kamari Village, Santorini, Greece
*** 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 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)
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 Caâ€™ 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 avail
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 here.