Big Data

Big Data Research 4TU.AMI
4TU Delft
4TU Eindhoven
4TU Twente
4TU Wageningen

Big Data

Coordinators:
Nelly Litvak (UT), Alessandro Di Bucchianico and Laura Iapichino (TU/e), Frank van der Meulen (TUD) and Ron Wehrens (WUR).

Research:

Big Data promises to revolutionize our lives and our industry. However, a major challenge is extracting sensible information from massive data sets, using current hardware and software.  How can we make data uniform if it has so many properties. Data is nowadays easy to obtain, but it is sensitive and sometimes very noisy.

There is a lot of attention to big data from computer science, now the focus is shifting to mathematical challenges. We combine strengths in statistics and numerical analysis to tackle problems in big data. We make algorithms of complex networks. An example is a social network such as facebook or LinkedIn. As mathematicians in data science we analyse these networks and their properties and structures.

Big Data

Coordinators:
Nelly Litvak (UT), Alessandro Di Bucchianico and Laura Iapichino (TU/e), Frank van der Meulen (TUD) and Ron Wehrens (WUR).

Research:

Big Data promises to revolutionize our lives and our industry. However, a major challenge is extracting sensible information from massive data sets, using current hardware and software.  How can we make data uniform if it has so many properties. Data is nowadays easy to obtain, but it is sensitive and sometimes very noisy.

There is a lot of attention to big data from computer science, now the focus is shifting to mathematical challenges. We combine strengths in statistics and numerical analysis to tackle problems in big data. We make algorithms of complex networks. An example is a social network such as facebook or LinkedIn. As mathematicians in data science we analyse these networks and their properties and structures.

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Big Data

Big Data

Coordinators:
Nelly Litvak (UT), Alessandro Di Bucchianico and Laura Iapichino (TU/e), Frank van der Meulen (TUD) and Ron Wehrens (WUR).

Research:

Big Data promises to revolutionize our lives and our industry. However, a major challenge is extracting sensible information from massive data sets, using current hardware and software.  How can we make data uniform if it has so many properties. Data is nowadays easy to obtain, but it is sensitive and sometimes very noisy.

There is a lot of attention to big data from computer science, now the focus is shifting to mathematical challenges. We combine strengths in statistics and numerical analysis to tackle problems in big data. We make algorithms of complex networks. An example is a social network such as facebook or LinkedIn. As mathematicians in data science we analyse these networks and their properties and structures.

Big Data

Coordinators:
Nelly Litvak (UT), Alessandro Di Bucchianico and Laura Iapichino (TU/e), Frank van der Meulen (TUD) and Ron Wehrens (WUR).

Research:

Big Data promises to revolutionize our lives and our industry. However, a major challenge is extracting sensible information from massive data sets, using current hardware and software.  How can we make data uniform if it has so many properties. Data is nowadays easy to obtain, but it is sensitive and sometimes very noisy.

There is a lot of attention to big data from computer science, now the focus is shifting to mathematical challenges. We combine strengths in statistics and numerical analysis to tackle problems in big data. We make algorithms of complex networks. An example is a social network such as facebook or LinkedIn. As mathematicians in data science we analyse these networks and their properties and structures.