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 an Assistant Professor at the Faculty of Electrical Engineering, University of Sarajevo, in the Department of Computer Science. I truly enjoy working with students and teaching courses such as Practical Application of AI and Linear Algebra and Geometry. Guiding students as they connect theory with real-world applications is one of the most rewarding aspects of my work, and it constantly inspires me to push the boundaries of how computational mathematics and AI can be taught and applied.

In parallel with my academic role, over the past three years I worked with the Swedish startup Emulate Energy, a company dedicated to making renewable energy universally accessible. There, I contributed to accelerating the global transition to clean energy by applying data science and optimization to real-world challenges. This combination of academia and industry has shaped my perspective, allowing me to bring both practical insights and cutting-edge research into the classroom.

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.