GPU Computing and Machine Learning for solving high-dimensional BSDEs

My name is Lorenc Kapllani, I come from Albania. Currently, I’m following my first year of the PhD program in University of Wuppertal, group of Applied Mathematics and Numerical Analysis (AMNA). I completed the bachelor’s degree in Engineering Mathematics at the Polytechnic University of Tirana (Albania). My bachelor thesis was […]

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German-Slovakian Project MATTHIAS on Hamilton-Jacobi-Bellman Equations in Finance

  Bilateral German-Slovakian Project MATTHIAS – Modelling and Approximation Tools and Techniques for Hamilton-Jacobi-Bellman equations in finance and Innovative Approach to their Solution financed by DAAD and the Slovakian Ministry of Education (01/2020 – 12/2021) Scientific goals The project deals with qualitative and numerical analysis of nonlinear partial differential equations […]

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SCEE – 2020 – Eindhoven, The Netherlands. Scientific Computing in Electrical Engineering

Between Feb 16-20, 2020, the Conference on Scientific Computing in Electrical Engineering (SCEE-2020) took place in Eindhoven, The Netherlands. It appeared to be one of the last face-to-face conferences before the Corona pandemic really became active. Let me first address the conference series and this event itself. The SCEE conference […]

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New Book on Nanoeletronic Coupled Problems Solutions

The EU-funded research project fp7-nanoCOPS (Nanoeletronic Coupled Problems Solutions, 2013-2016) published an overview of outcomes in October 2019. The book has been published by Springer in the Series with ECMI, Mathematics in Industry. Involved partners from academia were: Bergische Universität Wuppertal, Technische Universität Darmstadt, Humboldt Universität zu Berlin, Universität Greifswald, […]

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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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