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TACC Training for Automotive Companies Creation

Lo scorso 29 novembre è stato pubblicato il bando per le candidature al progetto TACC Training for Automotive Companies Creation, percorso sperimentale e innovativo di orientamento e formazione all'imprenditorialità del settore automotive, in contesto interdisciplinare.
Il progetto è dedicato agli studenti delle lauree magistrali e ai dottorandi di UniMoRe e può rappresentare una interessante opportunità per acquisire competenze e soft skills in tema di innovazione e imprenditività, utili nel mondo del lavoro.
E' possibile scaricare presentazione sintetica , manifesto e call for applications.
Fino al 9 gennaio sarà possibile candidarsi per partecipare al progetto e l'inizio delle attività è previsto a marzo 2018. Ulteriori info al link automotiveacademy.unimore.it/tacc.

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Thesis Award

Thesis Award
Giovanni Simonini received the Award for the best PhD Thesis defended in an Italian University in 2016 from the IEEE Computer Society Italy Section Chapter Computer Science and Engineering with his PhD dissertaion titled "Loosely Schema-aware Techniques for Big Data Integration".
Giovanni obtained is PhD in the 2016 from the ICT International Doctorate of the University of Modena and Reggio Emilia (XXVIII cycle) under the supervision of Prof. Sonia Bergmaschi
The prize was awarded at the 3rd International Forum on Research and Technologies for Society and Industry (http://rtsi2017.ieeesezioneitalia.it)

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Seminar announcement

Title: "Adsorption of chalcogen-based aromatic organic molecules on metal and dielectric surfaces by self-assembly and molecular beam expitaxy"
Speaker Tingming Jiang
Affiliation DIEF, University of Modena and Reggio Emilia and Universite' de Paris Sud
in fulfillment of the requirements for the award of the doctoral degree, he will defend his PhD activity in front of the final evaluation Jury, presenting a talk titled
Date & Time Monday December 18, 2017 - 14:30
Venue Meeting Room, I floor, MO26 building, Department of Engineering E. Ferrari, Via Vivarelli 10, Modena

Seminar Announcement

Venerdì 15 Dicembre 2017, ore 14,00-16,00, nell'Aula P1.6, nell'ambito degli Insegnamenti di Big Data Analysis e Progettazione del Software del Corso di laurea magistrale in INGEGNERIA INFORMATICA, percorso Data Engineering and Analytics,  il dottore di ricerca Matteo Interlandi, terrà il seminario:
" Big data analytics beyond MapReduce"

Abstract: MapReduce was introduced by Google in 2004. Thanks to its functional programming abstraction and fault-tolerant distributed framework, MapReduce makes easy to write parallel programs. In 2004 MapReduce was mostly used for web indexing; however nowadays we are seeing different type of applications (relational, graphs or machine learning analytics for example) which does not fit well within the MapReduce paradigm. In this talk I will use some research projects I have been working on in the past years to (1) introduce Apache Spark and Apache REEF; (2) describe how relational, graphs and machine learning applications can be efficiently run at scale using such systems; and (3) illustrate system's pros, cons and design choices.

Each seminar allows to acquire a CFD

Seminar Announcement

Venerdì 15 Dicembre 2017, ore 16,30-18,00, nell'Aula P1.6, il dottore di ricerca Matteo Interlandi, terrà il Seminario:
“Quick Develoment Big Data Analytics Tools"

Abstract: Implementing data processing logic in Data-Intensive Scalable Computing (DISC) systems is a difficult and time consuming effort. Today’s DISC systems offer many special purpose programming models and Domain Specific Languages, but very little tooling for debugging and profiling programs. As a result, programmers spend countless hours in stitching together subprograms written using different APIs, and performing trial and error debugging using log traces as evidences. To aid this effort, in the last years I have help in building a set of tools allowing developers to reduce the overall time to market for their Big Data Analytics. In particular, in this talk I will describe how relational, graphs and machine learning applications can be efficiently run at scale using the tooling I contributed to develop."

Bio: Matteo Interlandi is a Research Scientist in the Cloud and Information Services Lab (CISL) at Microsoft, working on scalable Machine Learning Systems. Before Microsoft, he was a Postdoctoral Scholar in the CS Department at the University of California, Los Angeles. Prior to joining UCLA, he was Research Associate at the Qatar Computing Research Institute and at the Institute for Human and Machine Cognition. He obtained his PhD in Computer Science at the University of Modena and Reggio Emilia under the supervision of Sonia Bergamaschi.

Each seminar allows to acquire a CFD