KTH Royal Institute of Technology
MSc Energy Transition (previously known as CFAFE) student Maria Kolmer says that thanks to the programme’s mobility concept, she is way more confident at looking for employment in the European job market. For her master thesis, she developed a fault detection algorithm. It’s based on the pattern recognition in the energy consumption.
Why did you choose the MSc CFAFE programme?
I wanted to step out from my comfort zone and challenge myself in a new environment abroad. I knew I would have a unique chance for travelling around Europe and I was very determined to apply here. Also, nowadays the significant share of energy is still produced from fossil fuels – a smooth transition from fossil fuels to alternative fuels requires specialists who can combine those two fields. I chose my programme to better understand current technologies applied in energy market – and to also get to know modern, clean technologies based on the alternative energy sources. I know that my CV will stand out from others, increasing my chances in the European job market.
Why are you interested in sustainable energy?
I believe sustainable energy production is crucial for the environment. For many countries it is a still long-term goal – but it must be achieved. I’d like to take part in this transition, from current technologies to the more sustainable ones. In this way, I feel like I can make a contribution, even if it’s just a small, to the well being of future generations. My specific interests include data analysis and machine learning techniques. I believe that those modern computational systems have huge potential and can make big impact in the field of energy engineering.
Is there a special projects or a degree thesis that you are working on at the moment?
Thanks to the InnoEnergy, I started an internship with one of their industry partners SBB ENERGY in Poland. After the internship I was offered a part-time position. I was analysing data in the process of NOx reduction, which was really interesting work and I discovered that I love analysing and programming data!
For my master thesis, I developed a fault detection algorithm. It’s based on the pattern recognition in the energy consumption. I’m working on this with the cooperation of a Portuguese start-up company EnergyOT, which produces smart meters, which I explore utilising in my thesis for fault detection.
What is your best memory from your time with the Master’s School so far?
My best memories are connected to the field trips that we had in Poland. We started the semester with an integration weekend in the mountains nearby – where we got to know each other doing cool activities like driving quads and playing paintball. Also, one month later we went to see a hydropower plant in Alps in Austria, then a waste plant and a dam on the Malta River. It was really cool to explore this region and see these amazing structures.
How do you find the integration of business and entrepreneurship in the programme?
Out of all the additional courses that I had during my studies so far, I’ve benefited the most from the weekly entrepreneurship course organized by Católica Lisbon School of Business and Economics: “Entrepreneur in a Week: From Dawn to Pitch”. This course gave really good insight into the challenges that every entrepreneur faces.
Has the programme atmosphere give you any inspiration for products, services or companies?
Thanks to the programme’s mobility concept, I’m way more confident at looking for employment in the European job market. The unique feature of InnoEnergy is that they are in cooperation with both big industrial partners and start-ups. I’ve gotten a change to get to know both environments so I can choose the option I like better. I have also enjoyed meeting people from all over the world. This international atmosphere, where you are able to meet and discuss the energy challenges of all these different countries/continents, has really broadened my horizons. I feel I’m getting a very well rounded education that just would not have been possible somewhere else.