About

Hi there! I’m a mechanical engineer who fell in love with computational mathematics along the way. I’ve always been drawn to solving complex, challenging problems that push the limits of traditional engineering, and computational math has opened up a whole new world for me. It lets us dig deeper into the why and how of natural events, giving us a clearer, more concrete understanding of the world around us. Ever since I was a kid, I’ve been torn between my love for math and physics, so deciding on a career path wasn’t easy. In the end, I chose mechanical engineering because it’s such a versatile field—it’s given me the confidence to explore and succeed in different areas, all while staying true to my passion for problem-solving.

I am currently working as a Data Scientist at Emulate Energy, a company dedicated to making renewable energy universally accessible, where I contribute to accelerating the global transition to clean energy. Simultaneously, I hold an Assistant Professor position at the Faculty of Electrical Engineering, University of Sarajevo, in the Department of Computer Science. This dual engagement allows me to bridge the gap between industry and academia, applying cutting-edge research to real-world challenges while bringing practical industry insights into the academic environment. Balancing both roles enhances my ability to innovate and contribute to both fields, ensuring that the latest advancements in computational mathematics and data science directly impact both education and the renewable energy sector.

Before joining Emulate Energy, I was a postdoctoral researcher at Lund University’s Department of Computer Science, focusing on Bayesian Optimization under the supervision of Asst. Professor Luigi Nardi. This project, funded by WASP (Wallenberg AI, Autonomous Systems, and Software Programme), expanded my expertise in high-dimensional optimization problems.

Prior to that, in April 2020, I completed my Ph.D. at the Technical University of Denmark, in the Department of Applied Mathematics and Computer Science, under the guidance of Assoc. Professor Mirza Karamehmedović. My doctoral research was part of the DeRisk project, which aimed to reduce costs in offshore wind turbines by developing innovative design methods to quantify extreme wave loads—a complex challenge due to the high-dimensional nature of the numerical models involved.

During my Ph.D., I had the honor of spending six months at MIT, collaborating with Professor Youssef Marzouk, further refining my skills in uncertainty quantification and computational science.

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.