Mathias Mul – Floodlight Data
After 5 years working with applied data analytics in the steel industry, I decided to found Floodlight Data. I have worked in numerous agile project teams to understand and solve production and quality related problems. This experience gave me a practical and straight-forward way of thinking regarding big data. The method and approach to specific problems is key in making actual improvements. I have learnt when I have to use which skill in order to achieve the set goals of a project.
Down-to-earth data analytics is what drives me. There is a tremendous amount of business opportunities in the field of big data, artificial intelligence, machine learning, physical and statistical modelling, smart algorithms, dashboarding and data visualization. I am passionate about breaking down a problem into a structured, well-defined approach until the implementation has proven itself.
The path of independence has brought me to amazing projects. Whether I look at real-estate models for a housing corporation, or think about how to use satellite data to model soil organic carbon. When the deformation of car parts is of interest, or finding out novel ways of using glass fiber measurement technology. It is amazing to make use of my skills and knowledge and to be able to work on seemingly unrelated topics that in the core are always related by logic and structure.
History
2020-present
Floodlight Data Strategy and Support
2014-2020
TATA Steel IJmuiden
I had the initiative to start a practical R/Rstudio introductory course of which I designed all contents. Over 100 employees have followed this course in Tata IJmuiden. In addition, I gave taught in the Advanced Analytics bootcamp that has been introduced by the Advanced Analytics department in collaboration with McKinsey. I supported colleagues across the site in data engineering and data science using R and Rstudio.
I was involved with the technology of the Continuous Caster 23 in the steel plant. My main interest was the development and implementations of algorithms that are based on mould temperature measurements with fiber Bragg grating technology. I have initiated a cooperation with the supplier Primetals Austria for implementation. I have written and presented a paper on new algorithms for steel production during METEC ESTAD 2019, ‘Real-time Mould Temperature Control for the Purpose of Consistent Slab Quality’.
I did improvement projects in several multidisciplinary agile teams across different production plants on the site. I performed fact-based analysis on process data. My specialty was extracting and coupling data from various data sources, then processing and visualizing the results. The work included production trials and implementation of improvements.
2012-2014
MSc double degree
TU Delft Applied Mathematics, master thesis in modeling phase transformations in steel alloy
TU Berlin Scientific Computing
2008-2012
BSc degree
TU Delft Applied Mathematics
– minor in Finance (evaluating prices of financial products)
– Thesis resulting in publication ‘Semi-stochastic cell-level computational modeling of the immune system response to bacterial infections and the effects of antibiotics’