ECMI Webinar “Math for Industry 4.0 – Models, Methods and Big Data”, December 2 – 3, 2020

In a joint activity of the Special Interest Groups Mathematics for Big Data and Math for the Digital Factory of the European Consortium for Mathematics in Industry (ECMI) this workshop strives to bring together data scientists, mathematicians, and engineers from academia and industry to discuss recent developments in digital manufacturing. […]

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PRecision crop protECtion: deep learnIng and data fuSION

Current farming practices require a uniform application of pesticides in order to protect crop plants from pest and disease. These treatments are typically repeated at regular time intervals. However, it is well known that several pests and diseases exhibit an uneven spatial distribution, with typical patch structures evolving around localized […]

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ITWM Researcher Stefanie Schwaar Establishes New Research Group for Artificial Intelligence

Dr. Stefanie Schwaar from the Fraunhofer Institute for Industrial Mathematics ITWM won the BMBF’s call for tenders for funding among young female AI researchers. She will establish and head her own research group at the mathematical institute from August 2020. Under the title “EP-KI: Decision Support for Business Management Processes […]

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Improving tax collection with big data analytics

Tax evasion is one of the major obstacles to increasing the competitiveness of an economy. It directly and negatively affects the conditions for business activities in the market for the companies that legally declare and pay taxes, making their production costs, and, consequently, the price of their products and services […]

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Bigmath Advanced Course 4: Large scale and distributed optimization

The goal of the training course, realized within the H2020 Marie Skłodowska-Curie project Big Data Challenges for Mathematics, Grant Agreement No 812912,  is to provide an overview of tools and algorithms in the area of large scale and distributed optimization. An illustrative examples which help in understanding how optimization-based modelling can […]

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The Experts Method for the prediction of big data streams of energy flow

We have developed a method, called Experts Method, to forecast the evolution of a multivariate set of time series, of big dimension, and with partially censored data. It has been applied to the data provided by the H2020 Big Data Horizon Prize 2017 (http://ec.europa.eu/research/horizonprize/index.cfm?prize=bigdata). The data subject to the forecast […]

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BIGMATH: Stochastic Geometric modelling and 3D image analysis for human face prostheses

My name is Filipa Valdeira, I am from Lisbon (Portugal) where I have completed an Integrated Master in Aerospace Engineering, with a specialization in Systems and Control. During the last year of the degree, I conducted my Master’s Thesis on the topics of optimization and statistics. This sparked my interest […]

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BIGMATH: Mathematical morphology for the prediction of face expression transition

My name is Rongjiao Ji, I am currently a first-year PhD student in the PhD school in Mathematical Sciences, Universita’ degli Studi di Milano (Italy), and I am enrolled in the Marie Skłodowska-Curie Action – Innovative Training Network/European Industrial Doctorate BIGMATH. I received my master degree in Probability and Statistics […]

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The new Data Science Research Center at University of Milan

We are happy to announce the birth of the Data Science Research Center, a new coordinated research center of Università degli Studi di Milano. The primary objective of the Data Science Research Center (DSRC) is to integrate the competences and research activities in computer science, statistics and mathematics of the […]

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Two Research Technician positions at BCAM

Applications are invited for two research technician positions at BCAM, the Basque Center for Applied Mathematics. The selected candidates will work at BCAM’s Knowledge Transfer Unit (KTU). The aim of the KTU is to develop mathematical solutions for scientific challenges based on real-life applications. The candidates will collaborate on knowledge […]

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