About
Hi, I am a mechanical engineer who found himself within computational mathematics. I find great inspiration in difficult and complex problems that challenge my way of thinking. Computational mathematics allows us to go beyond standard approaches in engineering. We start understanding the background of natural events in a more concrete way. Since my young age, I was attached to mathematics and physics. So, it was hard for me to decide which path to take. Eventually, I went for mechanical engineering which really allows someone to easily migrate to other fields while being confident in his/her abilities.
I am currently working as a Data Scientist at Emulate Energy with the purpose to make renewable energy 100% accessible to the entire world. Emulate was founded in 2020 with the mission to accelerate the global transition to clean energy. Before joing Emulate Energy, I was a postdoc researcher at the Lund University, Department of Computer Science on Bayesian Optimization under the supervision of Asst. Professor Luigi Nardi. The project was financed by WASP (Wallenberg AI, Autonomous System and Software Programme). Previously, in April 2020, I have finished successfully the Ph.D. project at the Technical University of Denmark, Department of Applied Mathematics and Computer Science, under the supervision of Assoc. Professor Mirza Karamehmedović. The project was a part of a larger project called DeRisk with the goal to reduce the cost within offshore wind turbines by providing new design methods to quantify extreme wave loads. The problem was very complex to handle as it required a large number of features with a numerical model that is expensive and difficult to use. During this period, I was honored to visit MIT for 6 months to work and collaborate with Professor Youssef Marzouk.
My research interests include:
- Uncertainty quantification
- Machine learning
- Hyperparameter optimization
- High-dimensional problems
- Rare events
For more information check my curriculum vitae and a list of scientific publications.