Bio

Daniele Foroni, Ph.D., is a Senior Full-Stack Data Scientist at Stats Perform, working on creating models on sport data to enhance the level of the analysis performed by the clubs, and by providing support to other custermers (e.g., deliverying new ways to present the sport event to the viewer through the broadcasting companies). Previously, he was working as Staff Big Data Research Engineer at the Huawei MRC (Munich Research Center) of Munich, Germany. There, I worked on smart cities solutions for traffic, creating models and algorithms to improve the defined KPIs (e.g., reduce the time spent within the car), as well as developing the micro-traffic simulator, CityMoS, together with the TUM Create team in Singapore, and collaborating with the EURECOM Research Center on data quality analysis of traffic solutions.

Daniele obtained his Ph.D. in Computer Science from the University of Trento with a thesis on the evaluation and the path to possibly improve the quality of the data at hand.

Here is my activity as reviewer and PC-member and some recent publications. For more details, see also my Google Scholar and ResearchGate profile.

Teaching, Lectures, and Talks

• 2021, Lecturer, Apache Spark - The Art of Distributing, University of Trento, Italy
• 2021, Invited Talk, Apache Spark - Notions and Lab Session, Utrecht University, The Netherlands

• 2020, Invited Talk, From Hadoop to Spark - A Big Data Journey, University of Trento, Italy

• 2015 - 2019, TA for Big Data, M.Sc. in Computer Science, University of Trento, Italy; prof. Yannis Velegrakis
• 2015 - 2019, TA for Data Mining, M.Sc. in Computer Science, University of Trento, Italy; prof. Yannis Velegrakis
• 2015 - 2019, TA for Big Data, M.Sc. in Computer Science, University of Trento, Italy; prof. Roberto Zunino