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*********************************************** 7th INTERNATIONAL SCHOOL ON BIG DATA BigDat 2023 Summer Las Palmas de Gran Canaria, Spain July 17-21, 2023 https://bigdat.irdta.eu/2023su *********************************************** Co-organized by: University of Las Palmas de Gran Canaria Institute for Research Development, Training and Advice - IRDTA Brussels/London *********************************************** Early registration: January 14, 2023 *********************************************** FRAMEWORK: 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 the opportunity to attend lectures in the program of DeepLearn 2023 Summer as well if they are interested. SCOPE: BigDat 2023 Summer 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. 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 research 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, infrastructure, 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 16 four-hour and a half courses and 2 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract 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 sessions with industrial and employment profiles. ADDRESSED TO: Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, BigDat 2023 Summer 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 to and discuss with major researchers, industry leaders and innovators. VENUE: BigDat 2023 Summer will take place in Las Palmas de Gran Canaria, on the Atlantic Ocean, with a mild climate throughout the year, sandy beaches and a renowned carnival. The venue will be: Institución Ferial de Canarias Avenida de la Feria, 1 35012 Las Palmas de Gran Canaria https://www.infecar.es/ STRUCTURE: 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 from 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 venue. 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. KEYNOTE SPEAKERS: Valerie Daggett (University of Washington), tba Sander Klous (University of Amsterdam), tba PROFESSORS AND COURSES: (to be completed) Paolo Addesso (University of Salerno), [introductory/intermediate] Data Fusion for Remotely Sensed Data Marcelo Bertalmío (Spanish National Research Council), [introductory] The Standard Model of Vision and Its Limitations: Implications for Imaging, Vision Science and Artificial Neural Networks Gianluca Bontempi (Free University of Brussels), [intermediate/advanced] Machine Learning for Big Data Analytics: from Prediction to Causal Inference Altan Çakir (Istanbul Technical University), [introductory/intermediate] Introduction to Distributed Deep Learning with Apache Spark Ian Fisk (Flatiron Institute), tba Ravi Kumar (Google), [intermediate/advanced] Differential Privacy Wladek Minor (University of Virginia), [introductory/advanced] Big Data in Biomedical Sciences José M.F. Moura (Carnegie Mellon University), [introductory/intermediate] Graph Signal Processing and Geometric Learning Panos Pardalos (University of Florida), [intermediate/advanced] Data Analytics for Massive Networks Ramesh Sharda (Oklahoma State University), [introductory/intermediate] Network-Based Health Analytics Steven Skiena (Stony Brook University), [introductory/intermediate] Word and Graph Embeddings for Machine Learning Ana Trisovic (Harvard University), [introductory/advanced] Reproducible Research, Best Practices and Big Data Management Sebastián Ventura (University of Córdoba), [tba] Supervised Descriptive Pattern Mining 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 the title, authors, and summary of the research to da...@irdta.eu by July 9, 2023. 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. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to da...@irdta.eu by July 9, 2023. EMPLOYER SESSION: 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-page .pdf leaflet with a brief description of the organization 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 da...@irdta.eu by July 9, 2023. ORGANIZING COMMITTEE: Carlos Martín-Vide (Tarragona, program chair) Sara Morales (Brussels) David Silva (London, organization chair) REGISTRATION: It has to be done at https://bigdat.irdta.eu/2023su/registration/ The selection of 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 as well as eventually courses in DeepLearn 2023 Summer. 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 tool disabled when the capacity of the venue will have got 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. The fees for on site and for online participation are the same. ACCOMMODATION: Accommodation suggestions will be available in due time at https://bigdat.irdta.eu/2023su/accommodation/ CERTIFICATE: A certificate of successful participation in the event will be delivered indicating the number of hours of lectures. Participants will be recognized 2 ECTS credits by University of Las Palmas de Gran Canaria. QUESTIONS AND FURTHER INFORMATION: da...@irdta.eu ACKNOWLEDGMENTS: Cabildo de Gran Canaria Universidad de Las Palmas de Gran Canaria - Fundación Parque Científico Tecnológico Rovira i Virgili University Institute for Research Development, Training and Advice – IRDTA, Brussels/London
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