Swimming in Data

This is a blog about data science and this is a brief intro on how I got here.

I started simulating some basic problems in chaos theory when I was 16ish. So, to no ones surprise, I went to study mathematical physics when turned 18 at Radboud University in Nijmegen, Netherlands. After completing my master's degree, I realized I wanted to focus more on the practical applications of mathematics. I applied and got accepted to a PhD position in Industrial Engineering focusing on Predictive Maintenance at Eindhoven University of Technology. You can find the results here.

During my PhD, I learned much about data analysis and optimization in the context of Predictive Maintenance. As part of my PhD, I visited Tepper School of Business in Pittsburgh, Pennsylvania, where I researched the trade-off between refurbishing old power plants or building new ones using mathematical optimization. One of the big challenges observed in practice for both maintenance and power plant economics is the acquisition of data and how to use it effectively. After my PhD, I went to work at EyeOn as a data scientist, where I work on data analysis and forecasting in supply chains.

I got inspired by the recent developments in data science and AI to learn more about how I can use it. This blog shares my learning journey on how to apply data science to make an impact.