Dr. Pawan Goyal awarded for best Ph.D. Thesis in Mathematics in 2018

Pawan

Dr.Pawan Goyal, mathematician and alumnus of the International Max Planck Research School Magdeburg, was awarded the prize for the best Ph.D. thesis in 2018 within the Faculty of Mathematics by the Otto von Guericke University Magdeburg. His thesis topic is the System-Theoretic Model Order Reduction for Bilinear and Quadratic-Bilinear Systems.

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August 2018

BiGmax job offers.


31/08/2017
The electronica blog posted an article about BigMax. Link here.

10/08/2017
The Vogel communication BigData Insider talks about BiGmax more.
25/07/2017
The Max Planck Society released a press note about BigMax. The full press release can be found here.

BigMax research scope and the participating institutes

 
Materials science is entering an era where the growth of data from experiments and calculations is expanding beyond a level that is properly processable by established scientific methods. Dealing with this big data is not just a technical challenge but much more it is a great chance. Big-data analytics will revolutionize new material discovery and will make the successful search of structure-property relationships among multiple lengthscales and timescales possible.
Thus far, the search for new materials for new applications was limited to educated guesses mostly based on selective experiments. By tackling this big data challenge with high-speed computing  extremely large, disparate databases and large-scale computations have to be dealt with. But recent advances in data mining will allow pattern recognition and pattern prediction in an unprecedented way. The outcome of big-data-driven materials science approaches will then impact the way experiments and data analyses are done.

BiGmax scope

 

Materials science is entering an era where the growth of data from experiments and calculations is expanding beyond a level that is properly processable by established scientific methods. Dealing with this big data is not just a technical challenge but much more it is a great chance. Big-data analytics will revolutionize new material discovery and will make the successful search of structure-property relationships among multiple lengthscales and timescales possible.
Thus far, the search for new materials for new applications was limited to educated guesses mostly based on selective experiments. By tackling this big data challenge with high-speed computing  extremely large, disparate databases and large-scale computations have to be dealt with. But recent advances in data mining will allow pattern recognition and pattern prediction in an unprecedented way. The outcome of big-data-driven materials science approaches will then impact the way experiments and data analyses are done.
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