Since July 1st 2016 I am with Data Reply GmbH (Reply AG) in München (Germany) as a Machine-Learning and Data Engineer, and I mainly work with the Cloudera (Hadoop, Hive, Impala, Hue, Spark, HBase, Ooozie) and Confluent (Kafka) stacks. The company has a focus on Big Data Science and Engineering. Beyond the hype, what we do is to design software artefacts for large-scale computing clusters, which can run AI algorithms on massive datasets in order to deliver business insights and services.

For the period February-June 2016 I have been IT Consultant for Smart Energy solutions at Power Reply GmbH (Reply AG). There I worked on mobile energy analytics projects with German energy utilities, focusing mostly on Android development and REST/JSON web services running on the Spring framework. I focused on demand-related analytics, specifically empowered by load disaggregation and mostly targeted to residential customers.
Until January 2016, I have been doing research on power trading and brokerage for Microgrids, supported by a research scholarship funded by the Alpen-Adria-Universität Klagenfurt. I eventually defended my PhD dissertation in September 2016.
In the period running from October 2012 to August 2015 I have been with the Lakeside Labs, a research cluster focusing on self-organising systems, namely working for the MONERGY Interreg IV project and the Smart Grid Lab. There I worked on intelligent energy applications in Smart homes, namely on solutions to improve energy awareness and facilitate the integration of renewable energy generation.
In June 2012, I received a Master in Computer Science from Reykjavik University (Iceland) and University of Camerino (Italy). During my first year in Camerino, I focused on distributed and multi agent systems. I spent my second year at Reykjavik University in Iceland. I am a former student of the Center for Analysis and Design of Intelligent Agents (CADIA), where I wrote my thesis and I attended courses on Artificial Intelligence. My project dealt with the implementation of an Early Warning System for Ambient Assisted Living, basically a context-aware agent that, given a description of the environment as input, is able to autonomously evaluate the danger level of states and prevent users from getting too close to such dangers. Together with other 7 recipients, I was awarded for this project the best MS thesis award by the Marche regional government.
In 2010, I graduated as a B.S. in Applied Computer Science with focus on Embedded Systems at “Carlo Bo” University of Urbino. I have attended courses for designing embedded systems (e.g. digital electronics, electronic design automation, architectures and communication), as well as multimedia systems (e.g. multimedia processing, languages and applications, Information Systems). My final project concerned the use of Contiki OS for measuring environmental parameters in internet-of-things applications.
In 2009, I spent 3 months as intern software engineer for Townet, a leading company in wireless broadband networks in the ISM band. In this period, I had the chance to participate to the complete hardware and software development process and get an overall understanding of startup companies. Previously, I have worked as intern for companies involved in electronics and automation, as well as web development.

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