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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Short description of portfolio item number 1
Short description of portfolio item number 2
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
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Lecture at the Unstructured and Streaming Data Engineering course (Milano, Italy) as part of the Computer Science 1nd year Master Program of Politecnico of Milano 2019-2020.
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Lecture about Supervised Machine Learning at a Data Science Professional Training Course (Cefriel, Milano, Italy).
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Lecture about Anomaly Detection at a Data Science Professional Training Course (Cefriel, Milano, Italy).
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Lecture about Streaming Machine Learning at a Data Science Professional Training Course (Cefriel, Milano, Italy).
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Online seminar about Streaming Machine Learning at Universidad Politécnica de Madrid (Madrid, Spain).
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Lecture about Anomaly Detection at a Data Science Professional Training Course (Cefriel, Milano, Italy).
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Lecture about Anomaly Detection at a Data Science Professional Training Course (Cefriel, Milano, Italy).
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Lecture at the Streaming Data Analytics course (Milano, Italy) as part of the Computer Science 1nd year Master Program of Politecnico of Milano 2021-2022.
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Session Chair of Big Data Learning and Analytics at IEEE International Conference of Big Data 2021.
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Lecture about Anomaly Detection at a Data Science Professional Training Course (Cefriel, Milano, Italy).
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Lecture about Streaming Machine Learning at a Data Science Professional Training Course (Cefriel, Milano, Italy).
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Lecture about Anomaly Detection at a Data Science Professional Training Course (Cefriel, Milano, Italy).
MSc course, Politecnico of Milano, DEIB, 2020
Teaching Assistant of Digital Project Management course. The course provides an overview of the roles, responsibilities, and management methods of the digital project manager. The course assumes no prior knowledge in management techniques and is intended to teach students how to develop approaches and styles of management for digital projects. The course assumes a basic understanding of software analysis, design and development techniques.
MSc course, Politecnico of Milano, DEIB, 2022
Teaching Assistant of Streaming Data Analytics course. The course provides the foundational concepts, methods, languages, and systems for ingesting, processing, and analyzing data that flows to enable real-time decisions. The course aims to the tame velocity dimensions of Big Data without forgetting the volume and variety dimensions.
MSc course, Politecnico of Milano, DEIB, 2023
Teaching Assistant of Streaming Data Analytics course. The course provides the foundational concepts, methods, languages, and systems for ingesting, processing, and analyzing data that flows to enable real-time decisions. The course aims to the tame velocity dimensions of Big Data without forgetting the volume and variety dimensions.