cHiPSet Training School 2017
Big Data Processing and Analytics in the Internet of Everything Era
Novi Sad, Serbia, 20-22 September 2017
cHiPSet is promoting a Training School on Big Data Processing and Analytics in the Internet of Everything Era. It mainly targets PhD students, researchers and skilled practitioners. The training school within COST Action IC1406 will be positioned at the crossroads where Big Data and High Performance Computing (HPC) meet, with a target towards applications of these areas in modern technology. School aims at presenting more intertwined connections between HPC frameworks and specific data intensive domains and applications.
Big data high value use cases arising from mobile phone data, IoT, multimedia content or other interesting sources will be explored. The overarching goal is to improve participants’ understanding on typical workflows in those use cases encompassing data sensing/collecting, processing, filtering, analytics, and results visualization. Such workflows demand for high-level parallel programming models and scalable solutions, sometimes running on scarce devices. HPC frameworks exploit parallelism and distributed computing to address speed and scale issues and to enable efficient turn of massively large data into valuable information and meaningful knowledge. Trainers coming from academia and industry will provide presentations with detailed descriptions of the selected data and applications, as well as hands on experience in leveraging big data frameworks on real world problems. At the end, participants will be able to efficiently turn massively large HPC data into valuable information and meaningful knowledge.
This training event is sponsored by COST Action cHiPSet and coorganised by Faculty of Sciences and BioSense Institute, Novi Sad, Serbia. This edition will take place in Novi Sad, Serbia from 20 to 22 September, 2017.
Kenth Engø-Monsen , Ph.D
Senior Research Scientist
Analytics and Artificial Intelligence
Dr. Kenth Engø-Monsen obtained his MSc in computational mathematics from the Norwegian University of Science and Technology (1995), his PhD in Computer Science from University of Bergen (2000), and a Master of Technology Management in Telecom Strategy (2001) from NTNU/BI. He joined Telenor Research after completing his PhD, and is currently a senior research scientist and data scientist with more than 15 years of experience in telecom. Dr. Engø-Monsen has extensive knowledge in the field of telecom data, social network analysis, and applied research using mobile data. He is the co-inventor on nine patents, the co-founder of one company, and has more than 60 publications at international conferences and peer-reviewed academic papers in mathematics, computer science, data science, and social sciences. Dr. Engø-Monsen is currently leading Telenor Group’s initiative on big data for social good, and his work can be found here.
Apostolos N. Papadopoulos , Ph.D
Data Science & Engineering Lab
Aristotle University of Thessaloniki
Apostolos N. Papadopoulos (http://delab.csd.auth.gr/~apostol) received his 5-year Diploma degree in Computer Science and Engineering from the University of Patras and his Ph.D. degree from Aristotle University of Thessaloniki in 1994 and 2000 respectively. His research interests include databases, data mining and big data analytics. In 2008, the paper entitled “SkyGraph: An Algorithm for Important Subgraph Discovery”, received the award for the best Knowledge Discovery paper in ECML/PKDD 2008. Moreover, the paper “Metric-Based Top-k Dominating Queries” that was presented in EDBT 2014, has been selected as the best paper and an extended version appears in ACM Transactions on Database Systems. Prof. Papadopoulos has significant teaching experience for topics related to Big Data technologies like Hadoop, Spark and Cloud Computing in general. He is collaborating with the DaSciM groupof LiX at Ecole Polytechnique, University of Saclay, France and also with the Department of Environmental Sciences, Informatics and Statistics of Ca’Foscari University of Venice, Italy where he has given a series of lectures related to Big Data Analytics. Currently, he is an Associate Professor at the Department of Informatics of Aristotle University of Thessaloniki and a member of the Data Science and Engineering Lab.
Radu-Ioan Ciobanu , Ph.D
Faculty of Automatic Control and Computers
University Politehnica of Bucharest
Radu-Ioan Ciobanu is Lecturer and Researcher with the Computer Science department of the Faculty of Automatic Control and Computers, University Politehnica of Bucharest, Romania. He obtained his PhD with the highest distinction (summa cum laude) in the same faculty, with the thesis on “Context-Adaptive and Knowledge-Based Middleware for Mobile Collaborative Systems”. His research interests include pervasive and mobile networks, DTNs, opportunistic networks, cloud computing, leading to the publishing of papers and articles at important scientific journals and conferences. He is involved in several national/international research projects, and serves as Scientific Director for the H2020 project “Traffic and Data Offloading in Mobile Networks: TTOff” (MONROE 2nd Open Call). He also has an industrial expertise, being from the start with the VirtualMetrix startup company (developing smart adaptive power management solutions for Android-based devices) before joining the Academia.
Andrzej Beben , Ph.D
Institute of Telecommunications
Warsaw University of Technology
Ioannis Stavrinides ,
Cloud Solution Architect
SMS&P Practice Development Unit
Irene Kilanioti , Ph.D
Department of Computer Science
University of Cyprus
Irene Kilanioti received her PhD entitled “Improving Content Delivery with OSN-Awareness” from the Department of Computer Science, University of Cyprus, in 2017 under the supervision of Professor George A. Papadopoulos, and was granted the Greek State Scholarships Foundation scholarship during years 2012 – 2015. She received the B.Sc. degree in Informatics and Telecommunications (1998-2002) and M.Sc. degree in Advanced Information Systems (2002-2004) from the National Kapodistrian University of Athens, Greece (best student award). Her research interests include social networks and content delivery optimization, semantic web technologies, recommender systems, big data as well as adaptive educational software. She has 9 publications in refereed journals, book chapters, and conferences and is currently the reporter of cHiPSet Use Case 5 (WG1., Dr. Irene Kilanioti and Prof. George A. Papadopoulos, University of Cyprus, Department of Computer Science, “Delivering Social Multimedia Content with Scalability”). Since 2005 she works as a secondary education informatics teacher in Greek public schools (currently teaching in bilingual school in Germany) and has experience as adult educator, as well. She has previously worked as a software engineer in Vodafone Plc, and participated in inter-university projects. She is a member of the Cyprus Scientific and Technical Chamber (ΕΤΕΚ), Hellenic Informatics Union, ACM, IEEE, registered trainer of the National Center of Public Administration (EKDDA) in Greece.
Day 1 (20 September): – Big Data processing and applications
Kenth Engø-Monsen, Telenor Research, Norway, title of the talk: “Big Data for Social Good: Epidemics and disasters”
Apostolos Papadopoulos, Aristotle University of Thessaloniki, Greece, title of the talk: “Big Data Analytics using Apache Spark”
Day 2 (21 September): Collecting data, IoT technology
Radu-Ioan Ciobanu, University Politehnica of Bucharest, Romania, title of the talk: “Collecting and analysing data over smart participatory networks”
Andrzej Beben, Warsaw University of Technology, Poland, title of the talk: “IoT as an Ecosystem for Innovation”
Day 3 (22 September): – Cloud computing platform, Content delivery
Ioannis Stavrinides, Microsoft, title of the talk: “Azure Data Platform, Analytics and IoT”.
Irene Kilanioti, University of Cyprus, title of the talk: “Content delivery supported by social network-awareness”
The University of Novi Sad has more than 50.000 students and 5.000 employees and as such it is regional educational and research centre, recognized for its international openness and achievements. The main University Campus provides the University with a unique and beautiful setting – close to the city centre and even closer to the Danube River. Under the umbrella of university a lot of start-up and spin-off companies were founded, mostly in the IT sector.
Department of Mathematics and Informatics at the Faculty of Sciences is devoted to the education and research in the fields of mathematics and computing. The department recently started two year master program in Data Science through two modules: Data Analytics and High Performance Computing. The first module focuses on the extracting knowledge from data, utilizing machine learning, optimization, and signal processing tools, while the second focuses on the computer engineering issues of storing, managing and manipulating large volumes of data.
BioSense Institute coordinates, focuses and advances research and introduction and promotion of state-of-the-art ICT solutions for acquisition and processing of data in agriculture, ecology, environmental protection, water management and industry. With state-of-the-art equipment and – most important – with an international group of more than 60 enthusiastic researchers, BioSense Institute performs multidisciplinary research in the fields of micro and nanoelectronics, communications, signal processing, remote sensing, big data, robotics and biosystems. BioSense Institute is a member of the European Network of LivingLabs (ENoLL) and coordinates or participates in a large number of international research projects, including Horizon2020, FP7 and Eureka.
Information about cHiPSet Training School :
Ciprian Dobre, University Politehnica of Bucharest, Romania
Sanja Brdar, BioSense Institute, Serbia
Dzmitry Kliazovich, University of Luxembourg, Luxembourg
Joanna Kolodziej, Cracow University of Technology, Poland
Horacio Gonzalez-Velez, National College of Ireland, Ireland
Sanja Brdar, BioSense Institute
Srđan Škrbić, Faculty of Sciences, University of Novi Sad
Vladimir Crnojević, BioSense Institute
The event will take place at the University Campus of University of Novi Sad, at Faculty of Sciences, Novi Sad. Google map link: City of Novi Sad, Serbia
Address: Trg Dositeja Obradovica 3, Novi Sad, Serbia
How to reach Novi Sad
The International airport Airport Nikola Tesla, Belgrade is located 70 km from Novi Sad.
From the airport to Novi Sad :
You can reach Novi Sad from the airport approximately in an hour, by taxi service. There is no direct public transport line that is operating from the airport to Novi Sad. Alternatively, you can take bus line A1 from the airport to the Belgrade, and then take the bus or a train to Novi Sad. The bus or train ride from Belgrade to Novi Sad would take about 90 min. If you are coming with the evening flight, be aware that the bus line A1 operates only until 21h. After that time, there are no buses that are operating from the airport to Belgrade.
About Novi Sad
Novi Sad is the capital of the Autonomous Province of Vojvodina and the second largest city in Serbia. It is located in the southern part of the Pannonian Plane, 70 km from Belgrade airport, on the bank of Danube river. Novi Sad is industrial, cultural, scientific, educational, and administrative center of Vojvodina.
Novi Sad was founded in 1694, when Serb merchants formed a colony across the Danube from the Petrovaradin fortress, a Habsburg strategic military post. In the 18th and 19th centuries, it became an important trading and manufacturing center, as well as a center of Serbian culture of that period, earning the nickname of the Serbian Athens.
Novi Sad is nominated to be European Capital of culture in 2021 . It is well known by the famous summer music EXIT festival that holds place at Petrovaradin fortress every year in July for more than a decade.
More information about city of Novi Sad and sightseeing tips could be found on this link.