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 21 four-hour and a half 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.
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.
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:
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.
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 email@example.com by January 5, 2020.
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 firstname.lastname@example.org by January 5, 2020.
Firms/Universities 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 or department/institute 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 email@example.com by January 5, 2020.
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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 comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline.
A certificate of successful participation in the event will be delivered indicating the number of hours of lectures.
David Silva: firstname.lastname@example.org
Dipartimento di Ingegneria dell'Informazione, Università Politecnica delle Marche
Italian industrial association
CINI AIIS Lab (National AI Lab inside the University Italian Consortium)
Big Data Laboratory