I am a Senior Renewable Power Analyst at Veyt, developing long-term forecasts for the renewable sector, specifically for guarantees of origin, gas certificates, and power purchase agreements. We take a fundamental bottom-up approach with our data because, unlike other markets, prices are driven mainly by consumers’ willingness to pay.

Taking a fundamental approach allows us to analyse supply volumes, renewable capacity, and demand. With these analyses and drawing on the latest machine-learning and artificial intelligence techniques and methodologies, we create robust models.

I am an engineer by training, first mechanical and then aeronautical, so I like to take a mixed approach between practical and theoretical when solving problems. I have also worked as a research assistant and have taught software related to mechanical engineering.

In 2018, I completed a Master’s in renewables with my thesis focusing on hydropower and predicting floods using artificial intelligence. I then took a year at General Electric working on health research, developing an algorithm to calculate the volume of the left ventricle faster than existing labour-intensive techniques. After this, I had the opportunity to start a PhD studying and predicting wind power.

Throughout my career, I have been drawn to environmental solutions. Working in power markets means that I can track day-to-day changes as policy and markets move. This affords me with an understanding of the current state of the energy transition. I am an active contributor to the field, having been published seven times in various academic journals such as Energy, Physics (Conference series), Energy Science and Engineering, Vann and Heliyon.

At Veyt, my objective is to provide a benchmark for our clients so they can best decide how to profit from their investments in renewable assets. My problem-solving skills and my aptitude for software and mathematics means I know how to translate policy decisions into hard numbers.

I live in Norway and speak Arabic, English, and Norwegian.